Systems and methods to provide offers to travelers

ABSTRACT

A computing apparatus includes: a transaction handler configured to process transactions; a data warehouse configured to store transaction data recording the transactions and to store event data for travel related events; a pattern detector configured to identify correlation data relating transaction patterns in the transaction data and the events identified in the event data; a portal configured to, in response to an occurrence of a first event, provide merchants with a report of a predicted spending pattern, including the identification of a set of consumers, identified based on the correlation data and data identifying the first event; a score generator to compute a value score for a traveler based on transaction data of the traveler; and a data services platform configured to provide the value score to a hotelier in response to a transaction processed by the transaction handler to check in the traveler at the hotelier.

RELATED APPLICATIONS

The present application is a continuation application of U.S. patentapplication Ser. No. 13/093,499, filed Apr. 25, 2011 and entitled“Systems and Methods to Provide Offers to Travelers”, which claims thebenefit of the filing date of Prov. U.S. Pat. App. Ser. No. 61/327,517,filed Apr. 23, 2010 and entitled “Systems and Methods to Provide Offersto Travelers,” the entire disclosures of which applications are herebyincorporated herein by reference.

FIELD OF THE TECHNOLOGY

At least some embodiments of the present disclosure relate to providingoffers in general, and more particularly, providing offers based ontransaction data, such as records of payments made via credit cards,debit cards, prepaid cards, etc., and/or information based on orrelevant to the transaction data.

BACKGROUND

Millions of transactions occur daily through the use of payment cards,such as credit cards, debit cards, prepaid cards, etc. Correspondingrecords of the transactions are recorded in databases for settlement andfinancial recordkeeping (e.g., to meet the requirements of governmentregulations). Such data can be mined and analyzed for trends,statistics, and other analyses. Sometimes such data are mined forspecific advertising goals, such as to provide targeted offers toaccount holders, as described in PCT Pub. No. WO 2008/067543 A2,published on Jun. 5, 2008 and entitled “Techniques for Targeted Offers.”

U.S. Pat. App. Pub. No. 2009/0216579, published on Aug. 27, 2009 andentitled “Tracking Online Advertising using Payment Services,” disclosesa system in which a payment service identifies the activity of a userusing a payment card as corresponding with an offer associated with anonline advertisement presented to the user.

U.S. Pat. No. 6,298,330, issued on Oct. 2, 2001 and entitled“Communicating with a Computer Based on the Offline Purchase History ofa Particular Consumer,” discloses a system in which a targetedadvertisement is delivered to a computer in response to receiving anidentifier, such as a cookie, corresponding to the computer.

U.S. Pat. No. 7,035,855, issued on Apr. 25, 2006 and entitled “Processand System for Integrating Information from Disparate Databases forPurposes of Predicting Consumer Behavior,” discloses a system in whichconsumer transactional information is used for predicting consumerbehavior.

U.S. Pat. No. 6,505,168, issued on Jan. 7, 2003 and entitled “System andMethod for Gathering and Standardizing Customer Purchase Information forTarget Marketing,” discloses a system in which categories andsub-categories are used to organize purchasing information by creditcards, debit cards, checks and the like. The customer purchaseinformation is used to generate customer preference information formaking targeted offers.

U.S. Pat. No. 7,444,658, issued on Oct. 28, 2008 and entitled “Methodand System to Perform Content Targeting,” discloses a system in whichadvertisements are selected to be sent to users based on a userclassification performed using credit card purchasing data.

U.S. Pat. App. Pub. No. 2005/0055275, published on Mar. 10, 2005 andentitled “System and Method for Analyzing Marketing Efforts,” disclosesa system that evaluates the cause and effect of advertising andmarketing programs using card transaction data.

U.S. Pat. App. Pub. No. 2008/0217397, published on Sep. 11, 2008 andentitled “Real-Time Awards Determinations,” discloses a system forfacilitating transactions with real-time awards determinations for acardholder, in which the award may be provided to the cardholder as acredit on the cardholder's statement.

The disclosures of the above discussed patent documents are herebyincorporated herein by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments are illustrated by way of example and not limitation inthe figures of the accompanying drawings in which like referencesindicate similar elements.

FIG. 1 illustrates a system to provide services based on transactiondata according to one embodiment.

FIG. 2 illustrates the generation of an aggregated spending profileaccording to one embodiment.

FIG. 3 shows a method to generate an aggregated spending profileaccording to one embodiment.

FIG. 4 shows a system to provide information based on transaction dataaccording to one embodiment.

FIG. 5 illustrates a transaction terminal according to one embodiment.

FIG. 6 illustrates an account identifying device according to oneembodiment.

FIG. 7 illustrates a data processing system according to one embodiment.

FIG. 8 shows the structure of account data for providing loyaltyprograms according to one embodiment.

FIG. 9 shows a system to obtain purchase details according to oneembodiment.

FIG. 10 shows a system to provide loyalty programs according to oneembodiment.

FIG. 11 shows a method to administrate a loyalty program according toone embodiment.

FIG. 12 shows a system to provide offers according to one embodiment.

FIGS. 13-14 show methods to provide offers according to someembodiments.

FIG. 15 illustrates an example to provide offers according to oneembodiment.

DETAILED DESCRIPTION Introduction

In one embodiment, transaction data, such as records of transactionsmade via credit accounts, debit accounts, prepaid accounts, bankaccounts, stored value accounts and the like, is processed to provideinformation for various services, such as reporting, benchmarking,advertising, content or offer selection, customization, personalization,prioritization, etc.

In one embodiment, a transaction handler (e.g., a processor of creditcards, debit cards, prepaid cards) is configured to provide informationbased on, or derived from, transactional data to facilitate the processof providing offers to travelers or potential travelers. Details andexamples about the providing offers to travelers in one embodiment areprovided in the section entitled “TRAVEL.”

In one embodiment, an advertising network is provided based on atransaction handler to present personalized or targetedadvertisements/offers on behalf of advertisers. A computing apparatusof, or associated with, the transaction handler uses the transactiondata and/or other data, such as account data, merchant data, searchdata, social networking data, web data, etc., to develop intelligenceinformation about individual customers, or certain types or groups ofcustomers. The intelligence information can be used to select, identify,generate, adjust, prioritize, and/or personalize advertisements/offersto the customers. In one embodiment, the transaction handler is furtherautomated to process the advertisement fees charged to the advertisers,using the accounts of the advertisers, in response to the advertisingactivities.

In one embodiment, the computing apparatus correlates transactions withactivities that occurred outside the context of the transaction, such asonline advertisements presented to the customers that at least in partcause offline transactions. The correlation data can be used todemonstrate the success of the advertisements, and/or to improveintelligence information about how individual customers and/or varioustypes or groups of customers respond to the advertisements.

In one embodiment, the computing apparatus correlates, or providesinformation to facilitate the correlation of, transactions with onlineactivities of the customers, such as searching, web browsing, socialnetworking and consuming advertisements, with other activities, such aswatching television programs, and/or with events, such as meetings,announcements, natural disasters, accidents, news announcements, etc.

In one embodiment, the correlation results are used in predictive modelsto predict transactions and/or spending patterns based on activities orevents, to predict activities or events based on transactions orspending patterns, to provide alerts or reports, etc.

In one embodiment, a single entity operating the transaction handlerperforms various operations in the services provided based on thetransaction data. For example, in the presentation of the personalizedor targeted advertisements, the single entity may perform the operationssuch as generating the intelligence information, selecting relevantintelligence information for a given audience, selecting, identifying,adjusting, prioritizing, personalizing and/or generating advertisementsbased on selected relevant intelligence information, and facilitatingthe delivery of personalized or targeted advertisements, etc.Alternatively, the entity operating the transaction handler cooperateswith one or more other entities by providing information to theseentities to allow these entities to perform at least some of theoperations for presentation of the personalized or targetedadvertisements.

In one embodiment, a transaction handler is used to provide loyaltyprograms. For example, in one embodiment, the transaction handler is tohost third party loyalty programs for various different entities, suchas merchants, issuers, etc. An enrollment process is used to associatethe account identifiers of users with respective loyalty programs inwhich the users are enrolled. Account identification devices, such ascredit cards, debit cards, prepaid cards, etc., that are typically usedfor payment transactions processed via the transaction handler can alsobe used as member cards to identify membership for the respectiveloyalty programs.

In one embodiment, the transaction handler is to store loyalty programinformation, such as reward points, miles, cash back and purchasedetails, under the respective accounts identified by the accountidentification devices. For example, the transaction handler may storedata to track the accumulation of the benefits provided by the loyaltyprograms to the respective users enrolled in the loyalty programs, suchas reward points or miles. For example, the transaction handler mayprovide benefits, such as discounts, rebates, or cash back, viastatement credits.

In one embodiment, the transaction handler is to request the purchasedetails from merchants when the purchase details are relevant to theloyalty program; and the purchase details may be requested via responsesto authorization requests. In one embodiment, an authorization responseincludes the identification of one or more relevant loyalty programs inwhich the corresponding user is a member. Thus, the merchant may verifythe membership of the user based on the authorization response andprovide certain benefits without requiring a purchase.

In some embodiments, the benefits are determined based on the purchasedetails in accordance with loyalty program rules. The purchase detailsmay be received from the merchant in real time as the transaction iscompleted at the transaction terminal, or received in batch mode via afile transmitted from the merchant with requests to settle transactionsthat have been previously authorized.

Further details and examples about using a transaction handler inproviding loyalty programs according to one embodiment are provided inthe section entitled “LOYALTY PROGRAM.”

System

FIG. 1 illustrates a system to provide services based on transactiondata according to one embodiment. In FIG. 1, the system includes atransaction terminal (105) to initiate financial transactions for a user(101), a transaction handler (103) to generate transaction data (109)from processing the financial transactions of the user (101) (and thefinancial transactions of other users), a profile generator (121) togenerate transaction profiles (127) based on the transaction data (109)to provide information/intelligence about user preferences and spendingpatterns, a point of interaction (107) to provide information and/oroffers to the user (101), a user tracker (113) to generate user data(125) to identify the user (101) using the point of interaction (107), aprofile selector (129) to select a profile (131) specific to the user(101) identified by the user data (125), and an advertisement selector(133) to select, identify, generate, adjust, prioritize and/orpersonalize advertisements for presentation to the user (101) on thepoint of interaction (107) via a media controller (115).

In one embodiment, the system further includes a correlator (117) tocorrelate user specific advertisement data (119) with transactionsresulting from the user specific advertisement data (119). Thecorrelation results (123) can be used by the profile generator (121) toimprove the transaction profiles (127).

In one embodiment, the transaction profiles (127) are generated from thetransaction data (109) in a way as illustrated in FIGS. 2 and 3. Forexample, in FIG. 3, an aggregated spending profile (341) is generatedvia the factor analysis (327) and cluster analysis (329) to summarize(335) the spending patterns/behaviors reflected in the transactionrecords (301).

In one embodiment, a data warehouse (149) as illustrated in FIG. 4 iscoupled with the transaction handler (103) to store the transaction data(109) and other data, such as account data (111), transaction profiles(127) and correlation results (123). In FIG. 4, a portal (143) iscoupled with the data warehouse (149) to provide data or informationderived from the transaction data (109), in response to a query requestfrom a third party or as an alert or notification message.

In FIG. 4, the transaction handler (103) is coupled between an issuerprocessor (145) in control of a consumer account (146) and an acquirerprocessor (147) in control of a merchant account (148). An accountidentification device (141) is configured to carry the accountinformation (142) that identifies the consumer account (146) with theissuer processor (145) and provide the account information (142) to thetransaction terminal (105) of a merchant to initiate a transactionbetween the user (101) and the merchant.

FIGS. 5 and 6 illustrate examples of transaction terminals (105) andaccount identification devices (141). FIG. 7 illustrates the structureof a data processing system that can be used to implement, with more orfewer elements, at least some of the components in the system, such asthe point of interaction (107), the transaction handler (103), theportal (143), the data warehouse (149), the account identificationdevice (141), the transaction terminal (105), the user tracker (113),the profile generator (121), the profile selector (129), theadvertisement selector (133), the media controller (115), etc. Someembodiments use more or fewer components than those illustrated in FIGS.1 and 4-7, as further discussed in the section entitled “VARIATIONS.”

In one embodiment, the transaction data (109) relates to financialtransactions processed by the transaction handler (103); and the accountdata (111) relates to information about the account holders involved inthe transactions. Further data, such as merchant data that relates tothe location, business, products and/or services of the merchants thatreceive payments from account holders for their purchases, can be usedin the generation of the transaction profiles (127, 341).

In one embodiment, the financial transactions are made via an accountidentification device (141), such as financial transaction cards (e.g.,credit cards, debit cards, banking cards, etc.); the financialtransaction cards may be embodied in various devices, such as plasticcards, chips, radio frequency identification (RFID) devices, mobilephones, personal digital assistants (PDAs), etc.; and the financialtransaction cards may be represented by account identifiers (e.g.,account numbers or aliases). In one embodiment, the financialtransactions are made via directly using the account information (142),without physically presenting the account identification device (141).

Further features, modifications and details are provided in varioussections of this description.

Centralized Data Warehouse

In one embodiment, the transaction handler (103) maintains a centralizeddata warehouse (149) organized around the transaction data (109). Forexample, the centralized data warehouse (149) may include, and/orsupport the determination of, spending band distribution, transactioncount and amount, merchant categories, merchant by state, cardholdersegmentation by velocity scores, and spending within merchant target,competitive set and cross-section.

In one embodiment, the centralized data warehouse (149) providescentralized management but allows decentralized execution. For example,a third party strategic marketing analyst, statistician, marketer,promoter, business leader, etc., may access the centralized datawarehouse (149) to analyze customer and shopper data, to providefollow-up analyses of customer contributions, to develop propensitymodels for increased conversion of marketing campaigns, to developsegmentation models for marketing, etc. The centralized data warehouse(149) can be used to manage advertisement campaigns and analyze responseprofitability.

In one embodiment, the centralized data warehouse (149) includesmerchant data (e.g., data about sellers), customer/business data (e.g.,data about buyers), and transaction records (301) between sellers andbuyers over time. The centralized data warehouse (149) can be used tosupport corporate sales forecasting, fraud analysis reporting,sales/customer relationship management (CRM) business intelligence,credit risk prediction and analysis, advanced authorization reporting,merchant benchmarking, business intelligence for small business,rewards, etc.

In one embodiment, the transaction data (109) is combined with externaldata, such as surveys, benchmarks, search engine statistics,demographics, competition information, emails, etc., to flag key eventsand data values, to set customer, merchant, data or event triggers, andto drive new transactions and new customer contacts.

Transaction Profile

In FIG. 1, the profile generator (121) generates transaction profiles(127) based on the transaction data (109), the account data (111),and/or other data, such as non-transactional data, wish lists, merchantprovided information, address information, information from socialnetwork websites, information from credit bureaus, information fromsearch engines, and other examples discussed in U.S. patent applicationSer. No. 12/614,603, filed Nov. 9, 2009 and entitled “Analyzing LocalNon-Transactional Data with Transactional Data in Predictive Models,”the disclosure of which is hereby incorporated herein by reference.

In one embodiment, the transaction profiles (127) provide intelligenceinformation on the behavior, pattern, preference, propensity, tendency,frequency, trend, and budget of the user (101) in making purchases. Inone embodiment, the transaction profiles (127) include information aboutwhat the user (101) owns, such as points, miles, or other rewardscurrency, available credit, and received offers, such as coupons loadedinto the accounts of the user (101). In one embodiment, the transactionprofiles (127) include information based on past offer/coupon redemptionpatterns. In one embodiment, the transaction profiles (127) includeinformation on shopping patterns in retail stores as well as online,including frequency of shopping, amount spent in each shopping trip,distance of merchant location (retail) from the address of the accountholder(s), etc.

In one embodiment, the transaction handler (103) provides at least partof the intelligence for the prioritization, generation, selection,customization and/or adjustment of an advertisement for delivery withina transaction process involving the transaction handler (103). Forexample, the advertisement may be presented to a customer in response tothe customer making a payment via the transaction handler (103).

Some of the transaction profiles (127) are specific to the user (101),or to an account of the user (101), or to a group of users of which theuser (101) is a member, such as a household, family, company,neighborhood, city, or group identified by certain characteristicsrelated to online activities, offline purchase activities, merchantpropensity, etc.

In one embodiment, the profile generator (121) generates and updates thetransaction profiles (127) in batch mode periodically. In otherembodiments, the profile generator (121) generates the transactionprofiles (127) in real-time, or just in time, in response to a requestreceived in the portal (143) for such profiles.

In one embodiment, the transaction profiles (127) include the values fora set of parameters. Computing the values of the parameters may involvecounting transactions that meet one or more criteria, and/or building astatistically-based model in which one or more calculated values ortransformed values are put into a statistical algorithm that weightseach value to optimize its collective predictiveness for variouspredetermined purposes.

Further details and examples about the transaction profiles (127) in oneembodiment are provided in the section entitled “AGGREGATED SPENDINGPROFILE.”

Non-Transactional Data

In one embodiment, the transaction data (109) is analyzed in connectionwith non-transactional data to generate transaction profiles (127)and/or to make predictive models.

In one embodiment, transactions are correlated with non-transactionalevents, such as news, conferences, shows, announcements, market changes,natural disasters, etc. to establish cause and effect relationships topredict future transactions or spending patterns. For example,non-transactional data may include the geographic location of a newsevent, the date of an event from an events calendar, the name of aperformer for an upcoming concert, etc. The non-transactional data canbe obtained from various sources, such as newspapers, websites, blogs,social networking sites, etc.

In one embodiment, when the cause and effect relationships between thetransactions and non-transactional events are known (e.g., based onprior research results, domain knowledge, expertise), the relationshipscan be used in predictive models to predict future transactions orspending patterns, based on events that occurred recently or arehappening in real-time.

In one embodiment, the non-transactional data relates to events thathappened in a geographical area local to the user (101) that performedthe respective transactions. In one embodiment, a geographical area islocal to the user (101) when the distance from the user (101) tolocations in the geographical area is within a convenient range fordaily or regular travel, such as 20, 50 or 100 miles from an address ofthe user (101), or within the same city or zip code area of an addressof the user (101). Examples of analyses of local non-transactional datain connection with transaction data (109) in one embodiment are providedin U.S. patent application Ser. No. 12/614,603, filed Nov. 9, 2009 andentitled “Analyzing Local Non-Transactional Data with Transactional Datain Predictive Models,” the disclosure of which is hereby incorporatedherein by reference.

In one embodiment, the non-transactional data is not limited to localnon-transactional data. For example, national non-transactional data canalso be used.

In one embodiment, the transaction records (301) are analyzed infrequency domain to identify periodic features in spending events. Theperiodic features in the past transaction records (301) can be used topredict the probability of a time window in which a similar transactionwill occur. For example, the analysis of the transaction data (109) canbe used to predict when a next transaction having the periodic featurewill occur, with which merchant, the probability of a repeatedtransaction with a certain amount, the probability of exception, theopportunity to provide an advertisement or offer such as a coupon, etc.In one embodiment, the periodic features are detected through countingthe number of occurrences of pairs of transactions that occurred withina set of predetermined time intervals and separating the transactionpairs based on the time intervals. Some examples and techniques for theprediction of future transactions based on the detection of periodicfeatures in one embodiment are provided in U.S. Pat. App. Pub. No.2010/0280882, entitled “Frequency-Based Transaction Prediction andProcessing,” the disclosure of which is hereby incorporated herein byreference.

Techniques and details of predictive modeling in one embodiment areprovided in U.S. Pat. Nos. 6,119,103, 6,018,723, 6,658,393, 6,598,030,and 7,227,950, the disclosures of which are hereby incorporated hereinby reference.

In one embodiment, offers are based on the point-of-service to offereedistance to allow the user (101) to obtain in-person services. In oneembodiment, the offers are selected based on transaction history andshopping patterns in the transaction data (109) and/or the distancebetween the user (101) and the merchant. In one embodiment, offers areprovided in response to a request from the user (101), or in response toa detection of the location of the user (101). Examples and details ofat least one embodiment are provided in U.S. Pat. App. Pub. No.2008/0319843, entitled “Supply of Requested Offer Based on Point-ofService to Offeree Distance,” U.S. Pat. App. Pub. No. 2008/0300973,entitled “Supply of Requested Offer Based on Offeree TransactionHistory,” U.S. Pat. App. Pub. No. 2009/0076896, entitled “MerchantSupplied Offer to a Consumer within a Predetermined Distance,” U.S. Pat.App. Pub. No. 2009/0076925, entitled “Offeree Requested Offer Based onPoint-of Service to Offeree Distance,” and U.S. Pat. App. Pub. No.2010/0274627, entitled “Receiving an Announcement Triggered by LocationData,” the disclosures of which applications are hereby incorporatedherein by reference.

Targeting Advertisement

In FIG. 1, an advertisement selector (133) prioritizes, generates,selects, adjusts, and/or customizes the available advertisement data(135) to provide user specific advertisement data (119) based at leastin part on the user specific profile (131). The advertisement selector(133) uses the user specific profile (131) as a filter and/or a set ofcriteria to generate, identify, select and/or prioritize advertisementdata for the user (101). A media controller (115) delivers the userspecific advertisement data (119) to the point of interaction (107) forpresentation to the user (101) as the targeted and/or personalizedadvertisement.

In one embodiment, the user data (125) includes the characterization ofthe context at the point of interaction (107). Thus, the use of the userspecific profile (131), selected using the user data (125), includes theconsideration of the context at the point of interaction (107) inselecting the user specific advertisement data (119).

In one embodiment, in selecting the user specific advertisement data(119), the advertisement selector (133) uses not only the user specificprofile (131), but also information regarding the context at the pointof interaction (107). For example, in one embodiment, the user data(125) includes information regarding the context at the point ofinteraction (107); and the advertisement selector (133) explicitly usesthe context information in the generation or selection of the userspecific advertisement data (119).

In one embodiment, the advertisement selector (133) may query forspecific information regarding the user (101) before providing the userspecific advertisement data (119). The queries may be communicated tothe operator of the transaction handler (103) and, in particular, to thetransaction handler (103) or the profile generator (121). For example,the queries from the advertisement selector (133) may be transmitted andreceived in accordance with an application programming interface orother query interface of the transaction handler (103), the profilegenerator (121) or the portal (143) of the transaction handler (103).

In one embodiment, the queries communicated from the advertisementselector (133) may request intelligence information regarding the user(101) at any level of specificity (e.g., segment level, individuallevel). For example, the queries may include a request for a certainfield or type of information in a cardholder's aggregated spendingprofile (341). As another example, the queries may include a request forthe spending level of the user (101) in a certain merchant category overa prior time period (e.g., six months).

In one embodiment, the advertisement selector (133) is operated by anentity that is separate from the entity that operates the transactionhandler (103). For example, the advertisement selector (133) may beoperated by a search engine, a publisher, an advertiser, an ad network,or an online merchant. The user specific profile (131) is provided tothe advertisement selector (133) to assist in the customization of theuser specific advertisement data (119).

In one embodiment, advertising is targeted based on shopping patterns ina merchant category (e.g., as represented by a Merchant Category Code(MCC)) that has high correlation of spending propensity with othermerchant categories (e.g., other MCCs). For example, in the context of afirst MCC for a targeted audience, a profile identifying second MCCsthat have high correlation of spending propensity with the first MCC canbe used to select advertisements for the targeted audience.

In one embodiment, the aggregated spending profile (341) is used toprovide intelligence information about the spending patterns,preferences, and/or trends of the user (101). For example, a predictivemodel can be established based on the aggregated spending profile (341)to estimate the needs of the user (101). For example, the factor values(344) and/or the cluster ID (343) in the aggregated spending profile(341) can be used to determine the spending preferences of the user(101). For example, the channel distribution (345) in the aggregatedspending profile (341) can be used to provide a customized offertargeted for a particular channel, based on the spending patterns of theuser (101).

In one embodiment, mobile advertisements, such as offers and coupons,are generated and disseminated based on aspects of prior purchases, suchas timing, location, and nature of the purchases, etc. In oneembodiment, the size of the benefit of the offer or coupon is based onpurchase volume or spending amount of the prior purchase and/or thesubsequent purchase that may qualify for the redemption of the offer.Further details and examples of one embodiment are provided in U.S. Pat.App. Pub. No. 2008/0201226, entitled “Mobile Coupon Method and PortableConsumer Device for Utilizing Same,” the disclosure of which is herebyincorporated herein by reference.

In one embodiment, conditional rewards are provided to the user (101);and the transaction handler (103) monitors the transactions of the user(101) to identify redeemable rewards that have satisfied the respectiveconditions. In one embodiment, the conditional rewards are selectedbased on transaction data (109). Further details and examples of oneembodiment are provided in U.S. Pat. App. Pub. No. 2008/0082418,entitled “Consumer Specific Conditional Rewards,” the disclosure ofwhich is hereby incorporated herein by reference. The techniques todetect the satisfied conditions of conditional rewards can also be usedto detect the transactions that satisfy the conditions specified tolocate the transactions that result from online activities, such asonline advertisements, searches, etc., to correlate the transactionswith the respective online activities.

Further details about targeted offer delivery in one embodiment areprovided in U.S. Pat. App. Pub. No. 2010/0030644, and entitled “TargetedAdvertising by Payment Processor History of Cashless Acquired MerchantTransaction on Issued Consumer Account,” and in U.S. Pat. App. Pub. No.2011/0035280, entitled “Systems and Methods for Targeted AdvertisementDelivery, the disclosures of which applications are hereby incorporatedherein by reference.

Profile Matching

In FIG. 1, the user tracker (113) obtains and generates contextinformation about the user (101) at the point of interaction (107),including user data (125) that characterizes and/or identifies the user(101). The profile selector (129) selects a user specific profile (131)from the set of transaction profiles (127) generated by the profilegenerator (121), based on matching the characteristics of thetransaction profiles (127) and the characteristics of the user data(125). For example, the user data (125) indicates a set ofcharacteristics of the user (101); and the profile selector (129)selects the user specific profile (131) for a particular user or groupof users that best matches the set of characteristics specified by theuser data (125).

In one embodiment, the profile selector (129) receives the transactionprofiles (127) in a batch mode. The profile selector (129) selects theuser specific profile (131) from the batch of transaction profiles (127)based on the user data (125). Alternatively, the profile generator (121)generates the transaction profiles (127) in real-time; and the profileselector (129) uses the user data (125) to query the profile generator(121) to generate the user specific profile (131) in real-time, or justin time. The profile generator (121) generates the user specific profile(131) that best matches the user data (125).

In one embodiment, the user tracker (113) identifies the user (101)based on the user's activity on the transaction terminal (105) (e.g.,having visited a set of websites, currently visiting a type of webpages, search behavior, etc.).

In one embodiment, the user data (125) includes an identifier of theuser (101), such as a global unique identifier (GUID), a personalaccount number (PAN) (e.g., credit card number, debit card number, orother card account number), or other identifiers that uniquely andpersistently identify the user (101) within a set of identifiers of thesame type. Alternatively, the user data (125) may include otheridentifiers, such as an Internet Protocol (IP) address of the user(101), a name or user name of the user (101), or a browser cookie ID,which identify the user (101) in a local, temporary, transient and/oranonymous manner. Some of these identifiers of the user (101) may beprovided by publishers, advertisers, ad networks, search engines,merchants, or the user tracker (113). In one embodiment, suchidentifiers are correlated to the user (101) based on the overlapping orproximity of the time period of their usage to establish anidentification reference table.

In one embodiment, the identification reference table is used toidentify the account information (142) (e.g., account number (302))based on characteristics of the user (101) captured in the user data(125), such as browser cookie ID, IP addresses, and/or timestamps on theusage of the IP addresses. In one embodiment, the identificationreference table is maintained by the operator of the transaction handler(103). Alternatively, the identification reference table is maintainedby an entity other than the operator of the transaction handler (103).

In one embodiment, the user tracker (113) determines certaincharacteristics of the user (101) to describe a type or group of usersof which the user (101) is a member. The transaction profile of thegroup is used as the user specific profile (131). Examples of suchcharacteristics include geographical location or neighborhood, types ofonline activities, specific online activities, or merchant propensity.In one embodiment, the groups are defined based on aggregate information(e.g., by time of day, or household), or segment (e.g., by cluster,propensity, demographics, cluster IDs, and/or factor values). In oneembodiment, the groups are defined in part via one or more socialnetworks. For example, a group may be defined based on social distancesto one or more users on a social network website, interactions betweenusers on a social network website, and/or common data in social networkprofiles of the users in the social network website.

In one embodiment, the user data (125) may match different profiles at adifferent granularity or resolution (e.g., account, user, family,company, neighborhood, etc.), with different degrees of certainty. Theprofile selector (129) and/or the profile generator (121) may determineor select the user specific profile (131) with the finest granularity orresolution with acceptable certainty. Thus, the user specific profile(131) is most specific or closely related to the user (101).

In one embodiment, the advertisement selector (133) uses further data inprioritizing, selecting, generating, customizing and adjusting the userspecific advertisement data (119). For example, the advertisementselector (133) may use search data in combination with the user specificprofile (131) to provide benefits or offers to a user (101) at the pointof interaction (107). For example, the user specific profile (131) canbe used to personalize the advertisement, such as adjusting theplacement of the advertisement relative to other advertisements,adjusting the appearance of the advertisement, etc.

Browser Cookie

In one embodiment, the user data (125) uses browser cookie informationto identify the user (101). The browser cookie information is matched toaccount information (142) or the account number (302) to identify theuser specific profile (131), such as aggregated spending profile (341),to present effective, timely, and relevant marketing information to theuser (101) via the preferred communication channel (e.g., mobilecommunications, web, mail, email, point-of-sale (POS) terminal, etc.)within a window of time that could influence the spending behavior ofthe user (101). Based on the transaction data (109), the user specificprofile (131) can improve audience targeting for online advertising.Thus, customers will get better advertisements and offers presented tothem; and the advertisers will achieve better return-on-investment fortheir advertisement campaigns.

In one embodiment, the browser cookie that identifies the user (101) inonline activities, such as web browsing, online searching, and usingsocial networking applications, can be matched to an identifier of theuser (101) in account data (111), such as the account number (302) of afinancial payment card of the user (101) or the account information(142) of the account identification device (141) of the user (101). Inone embodiment, the identifier of the user (101) can be uniquelyidentified via matching IP address, timestamp, cookie ID and/or otheruser data (125) observed by the user tracker (113).

In one embodiment, a look up table is used to map browser cookieinformation (e.g., IP address, timestamp, cookie ID) to the account data(111) that identifies the user (101) in the transaction handler (103).The look up table may be established via correlating overlapping orcommon portions of the user data (125) observed by different entities ordifferent user trackers (113).

For example, in one embodiment, a first user tracker (113) observes thecard number of the user (101) at a particular IP address for a timeperiod identified by a timestamp (e.g., via an online payment process);and a second user tracker (113) observes the user (101) having a cookieID at the same IP address for a time period near or overlapping with thetime period observed by the first user tracker (113). Thus, the cookieID as observed by the second user tracker (113) can be linked to thecard number of the user (101) as observed by the first user tracker(113). The first user tracker (113) may be operated by the same entityoperating the transaction handler (103) or by a different entity. Oncethe correlation between the cookie ID and the card number is establishedvia a database or a look up table, the cookie ID can be subsequentlyused to identify the card number of the user (101) and the account data(111).

In one embodiment, the portal (143) is configured to observe a cardnumber of a user (101) while the user (101) uses an IP address to makean online transaction. Thus, the portal (143) can identify a consumeraccount (146) based on correlating an IP address used to identify theuser (101) and IP addresses recorded in association with the consumeraccount (146).

For example, in one embodiment, when the user (101) makes a paymentonline by submitting the account information (142) to the transactionterminal (105) (e.g., an online store), the transaction handler (103)obtains the IP address from the transaction terminal (105) via theacquirer processor (147). The transaction handler (103) stores data toindicate the use of the account information (142) at the IP address atthe time of the transaction request. When an IP address in the queryreceived in the portal (143) matches the IP address previously recordedby the transaction handler (103), the portal (143) determines that theuser (101) identified by the IP address in the request is the same user(101) associated with the account used in the transaction initiated atthe IP address. In one embodiment, a match is found when the time of thequery request is within a predetermined time period from the transactionrequest, such as a few minutes, one hour, a day, etc. In one embodiment,the query may also include a cookie ID representing the user (101).Thus, through matching the IP address, the cookie ID is associated withthe account information (142) in a persistent way.

In one embodiment, the portal (143) obtains the IP address of the onlinetransaction directly. For example, in one embodiment, a user (101)chooses to use a password in the account data (111) to protect theaccount information (142) for online transactions. When the accountinformation (142) is entered into the transaction terminal (105) (e.g.,an online store or an online shopping cart system), the user (101) isconnected to the portal (143) for the verification of the password(e.g., via a pop up window, or via redirecting the web browser of theuser (101)). The transaction handler (103) accepts the transactionrequest after the password is verified via the portal (143). Throughthis verification process, the portal (143) and/or the transactionhandler (103) obtain the IP address of the user (101) at the time theaccount information (142) is used.

In one embodiment, the web browser of the user (101) communicates theuser-provided password to the portal (143) directly without goingthrough the transaction terminal (105) (e.g., the server of themerchant). Alternatively, the transaction terminal (105) and/or theacquirer processor (147) may relay the password communication to theportal (143) or the transaction handler (103).

In one embodiment, the portal (143) is configured to identify theconsumer account (146) based on the IP address identified in the userdata (125) through mapping the IP address to a street address. Forexample, in one embodiment, the user data (125) includes an IP addressto identify the user (101); and the portal (143) can use a service tomap the IP address to a street address. For example, an Internet serviceprovider knows the street address of the currently assigned IP address.Once the street address is identified, the portal (143) can use theaccount data (111) to identify the consumer account (146) that has acurrent address at the identified street address. Once the consumeraccount (146) is identified, the portal (143) can provide a transactionprofile (131) specific to the consumer account (146) of the user (101).

In one embodiment, the portal (143) uses a plurality of methods toidentify consumer accounts (146) based on the user data (125). Theportal (143) combines the results from the different methods todetermine the most likely consumer account (146) for the user data(125).

Details about the identification of consumer account (146) based on userdata (125) in one embodiment are provided in U.S. Pat. App. Pub. No.2011/0093327, entitled “Systems and Methods to Match Identifiers,” thedisclosure of which is hereby incorporated herein by reference.

Close the Loop

In one embodiment, the correlator (117) is used to “close the loop” forthe tracking of consumer behavior across an on-line activity and an“off-line” activity that results at least in part from the on-lineactivity. In one embodiment, online activities, such as searching, webbrowsing, social networking, and/or consuming online advertisements, arecorrelated with respective transactions to generate the correlationresult (123) in FIG. 1. The respective transactions may occur offline,in “brick and mortar” retail stores, or online but in a context outsidethe online activities, such as a credit card purchase that is performedin a way not visible to a search company that facilitates the searchactivities.

In one embodiment, the correlator (117) is to identify transactionsresulting from searches or online advertisements. For example, inresponse to a query about the user (101) from the user tracker (113),the correlator (117) identifies an offline transaction performed by theuser (101) and sends the correlation result (123) about the offlinetransaction to the user tracker (113), which allows the user tracker(113) to combine the information about the offline transaction and theonline activities to provide significant marketing advantages.

For example, a marketing department could correlate an advertisingbudget to actual sales. For example, a marketer can use the correlationresult (123) to study the effect of certain prioritization strategies,customization schemes, etc. on the impact on the actual sales. Forexample, the correlation result (123) can be used to adjust orprioritize advertisement placement on a website, a search engine, asocial networking site, an online marketplace, or the like.

In one embodiment, the profile generator (121) uses the correlationresult (123) to augment the transaction profiles (127) with dataindicating the rate of conversion from searches or advertisements topurchase transactions. In one embodiment, the correlation result (123)is used to generate predictive models to determine what a user (101) islikely to purchase when the user (101) is searching using certainkeywords or when the user (101) is presented with an advertisement oroffer. In one embodiment, the portal (143) is configured to report thecorrelation result (123) to a partner, such as a search engine, apublisher, or a merchant, to allow the partner to use the correlationresult (123) to measure the effectiveness of advertisements and/orsearch result customization, to arrange rewards, etc.

Illustratively, a search engine entity may display a search page withparticular advertisements for flat panel televisions produced bycompanies A, B, and C. The search engine entity may then compare theparticular advertisements presented to a particular consumer withtransaction data of that consumer and may determine that the consumerpurchased a flat panel television produced by Company B. The searchengine entity may then use this information and other informationderived from the behavior of other consumers to determine theeffectiveness of the advertisements provided by companies A, B, and C.The search engine entity can determine if the placement, appearance, orother characteristic of the advertisement results in actual increasedsales. Adjustments to advertisements (e.g., placement, appearance, etc.)may be made to facilitate maximum sales.

In one embodiment, the correlator (117) matches the online activitiesand the transactions based on matching the user data (125) provided bythe user tracker (113) and the records of the transactions, such astransaction data (109) or transaction records (301). In anotherembodiment, the correlator (117) matches the online activities and thetransactions based on the redemption of offers/benefits provided in theuser specific advertisement data (119).

In one embodiment, the portal (143) is configured to receive a set ofconditions and an identification of the user (101), determine whetherthere is any transaction of the user (101) that satisfies the set ofconditions, and if so, provide indications of the transactions thatsatisfy the conditions and/or certain details about the transactions,which allows the requester to correlate the transactions with certainuser activities, such as searching, web browsing, consumingadvertisements, etc.

In one embodiment, the requester may not know the account number (302)of the user (101); and the portal (143) is to map the identifierprovided in the request to the account number (302) of the user (101) toprovide the requested information. Examples of the identifier beingprovided in the request to identify the user (101) include anidentification of an iFrame of a web page visited by the user (101), abrowser cookie ID, an IP address and the day and time corresponding tothe use of the IP address, etc.

The information provided by the portal (143) can be used in pre-purchasemarketing activities, such as customizing content or offers,prioritizing content or offers, selecting content or offers, etc., basedon the spending pattern of the user (101). The content that iscustomized, prioritized, selected, or recommended may be the searchresults, blog entries, items for sale, etc.

The information provided by the portal (143) can be used inpost-purchase activities. For example, the information can be used tocorrelate an offline purchase with online activities. For example, theinformation can be used to determine purchases made in response to mediaevents, such as television programs, advertisements, news announcements,etc.

Details about profile delivery, online activity to offline purchasetracking, techniques to identify the user specific profile (131) basedon user data (125) (such as IP addresses), and targeted delivery ofadvertisement/offer/benefit in some embodiments are provided in U.S.Pat. App. Pub. No. 2011/0035278, filed Aug. 3, 2010 and entitled“Systems and Methods to Deliver Targeted Advertisements to Audience,”the disclosure of which application is incorporated herein by reference.

Matching Advertisement & Transaction

In one embodiment, the correlator (117) is configured to receiveinformation about the user specific advertisement data (119), monitorthe transaction data (109), identify transactions that can be consideredresults of the advertisement corresponding to the user specificadvertisement data (119), and generate the correlation result (123), asillustrated in FIG. 1.

When the advertisement and the corresponding transaction both occur inan online checkout process, a website used for the online checkoutprocess can be used to correlate the transaction and the advertisement.However, the advertisement and the transaction may occur in separateprocesses and/or under control of different entities (e.g., when thepurchase is made offline at a retail store, whereas the advertisement ispresented outside the retail store). In one embodiment, the correlator(117) uses a set of correlation criteria to identify the transactionsthat can be considered as the results of the advertisements.

In one embodiment, the correlator (117) identifies the transactionslinked or correlated to the user specific advertisement data (119) basedon various criteria. For example, the user specific advertisement data(119) may include a coupon offering a benefit contingent upon a purchasemade according to the user specific advertisement data (119). The use ofthe coupon identifies the user specific advertisement data (119), andthus allows the correlator (117) to correlate the transaction with theuser specific advertisement data (119).

In one embodiment, the user specific advertisement data (119) isassociated with the identity or characteristics of the user (101), suchas global unique identifier (GUID), personal account number (PAN),alias, IP address, name or user name, geographical location orneighborhood, household, user group, and/or user data (125). Thecorrelator (117) can link or match the transactions with theadvertisements based on the identity or characteristics of the user(101) associated with the user specific advertisement data (119). Forexample, the portal (143) may receive a query identifying the user data(125) that tracks the user (101) and/or characteristics of the userspecific advertisement data (119); and the correlator (117) identifiesone or more transactions matching the user data (125) and/or thecharacteristics of the user specific advertisement data (119) togenerate the correlation result (123).

In one embodiment, the correlator (117) identifies the characteristicsof the transactions and uses the characteristics to search foradvertisements that match the transactions. Such characteristics mayinclude GUID, PAN, IP address, card number, browser cookie information,coupon, alias, etc.

In FIG. 1, the profile generator (121) uses the correlation result (123)to enhance the transaction profiles (127) generated from the profilegenerator (121). The correlation result (123) provides details onpurchases and/or indicates the effectiveness of the user specificadvertisement data (119).

In one embodiment, the correlation result (123) is used to demonstrateto the advertisers the effectiveness of the advertisements, to processincentive or rewards associated with the advertisements, to obtain atleast a portion of advertisement revenue based on the effectiveness ofthe advertisements, to improve the selection of advertisements, etc.

Coupon Matching

In one embodiment, the correlator (117) identifies a transaction that isa result of an advertisement (e.g., 119) when an offer or benefitprovided in the advertisement is redeemed via the transaction handler(103) in connection with a purchase identified in the advertisement.

For example, in one embodiment, when the offer is extended to the user(101), information about the offer can be stored in association with theaccount of the user (101) (e.g., as part of the account data (111)). Theuser (101) may visit the portal (143) of the transaction handler (103)to view the stored offer.

The offer stored in the account of the user (101) may be redeemed viathe transaction handler (103) in various ways. For example, in oneembodiment, the correlator (117) may download the offer to thetransaction terminal (105) via the transaction handler (103) when thecharacteristics of the transaction at the transaction terminal (105)match the characteristics of the offer.

After the offer is downloaded to the transaction terminal (105), thetransaction terminal (105) automatically applies the offer when thecondition of the offer is satisfied in one embodiment. Alternatively,the transaction terminal (105) allows the user (101) to selectivelyapply the offers downloaded by the correlator (117) or the transactionhandler (103). In one embodiment, the correlator (117) sends remindersto the user (101) at a separate point of interaction (107) (e.g., amobile phone) to remind the user (101) to redeem the offer. In oneembodiment, the transaction handler (103) applies the offer (e.g., viastatement credit), without having to download the offer (e.g., coupon)to the transaction terminal (105). Examples and details of redeemingoffers via statement credit are provided in U.S. Pat. App. Pub. No.2010/0114686, entitled “Real-Time Statement Credits and Notifications,”the disclosure of which is hereby incorporated herein by reference.

In one embodiment, the offer is captured as an image and stored inassociation with the account of the user (101). Alternatively, the offeris captured in a text format (e.g., a code and a set of criteria),without replicating the original image of the coupon.

In one embodiment, when the coupon is redeemed, the advertisementpresenting the coupon is correlated with a transaction in which thecoupon is redeemed, and/or is determined to have resulted in atransaction. In one embodiment, the correlator (117) identifiesadvertisements that have resulted in purchases, without having toidentify the specific transactions that correspond to theadvertisements.

Details about offer redemption via the transaction handler (103) in oneembodiment are provided in U.S. Pat. App. Pub. No. 2011/0125565,entitled “Systems and Methods for Multi-Channel Offer Redemption,” thedisclosure of which is hereby incorporated herein by reference.

On ATM & POS Terminal

In one example, the transaction terminal (105) is an automatic tellermachine (ATM), which is also the point of interaction (107). When theuser (101) approaches the ATM to make a transaction (e.g., to withdrawcash via a credit card or debit card), the ATM transmits accountinformation (142) to the transaction handler (103). The accountinformation (142) can also be considered as the user data (125) toselect the user specific profile (131). The user specific profile (131)can be sent to an advertisement network to query for a targetedadvertisement. After the advertisement network matches the user specificprofile (131) with user specific advertisement data (119) (e.g., atargeted advertisement), the transaction handler (103) may send theadvertisement to the ATM, together with the authorization for cashwithdrawal.

In one embodiment, the advertisement shown on the ATM includes a couponthat offers a benefit that is contingent upon the user (101) making apurchase according to the advertisement. The user (101) may view theoffer presented on a white space on the ATM screen and select to load orstore the coupon in a storage device of the transaction handler (103)under the account of the user (101). The transaction handler (103)communicates with the bank to process the cash withdrawal. After thecash withdrawal, the ATM prints the receipt, which includes aconfirmation of the coupon, or a copy of the coupon. The user (101) maythen use the coupon printed on the receipt. Alternatively, when the user(101) uses the same account to make a relevant purchase, the transactionhandler (103) may automatically apply the coupon stored under theaccount of the user (101), automatically download the coupon to therelevant transaction terminal (105), or transmit the coupon to themobile phone of the user (101) to allow the user (101) to use the couponvia a display of the coupon on the mobile phone. The user (101) mayvisit a web portal (143) of the transaction handler (103) to view thestatus of the coupons collected in the account of the user (101).

In one embodiment, the advertisement is forwarded to the ATM via thedata stream for authorization. In another embodiment, the ATM makes aseparate request to a server of the transaction handler (103) (e.g., aweb portal) to obtain the advertisement. Alternatively, or incombination, the advertisement (including the coupon) is provided to theuser (101) at separate, different points of interactions, such as via atext message to a mobile phone of the user (101), via an email, via abank statement, etc.

Details of presenting targeted advertisements on ATMs based onpurchasing preferences and location data in one embodiment are providedin U.S. Pat. App. Pub. No. 2010/0114677, entitled “System IncludingAutomated Teller Machine with Data Bearing Medium,” the disclosure ofwhich is hereby incorporated herein by reference.

In another example, the transaction terminal (105) is a POS terminal atthe checkout station in a retail store (e.g., a self-service checkoutregister). When the user (101) pays for a purchase via a payment card(e.g., a credit card or a debit card), the transaction handler (103)provides a targeted advertisement having a coupon obtained from anadvertisement network. The user (101) may load the coupon into theaccount of the payment card and/or obtain a hardcopy of the coupon fromthe receipt. When the coupon is used in a transaction, the advertisementis linked to the transaction.

Details of presenting targeted advertisements during the process ofauthorizing a financial payment card transaction in one embodiment areprovided in U.S. Pat. App. Pub. No. 2008/0275771, entitled “MerchantTransaction Based Advertising,” the disclosure of which is herebyincorporated herein by reference.

In one embodiment, the user specific advertisement data (119), such asoffers or coupons, is provided to the user (101) via the transactionterminal (105) in connection with an authorization message during theauthorization of a transaction processed by the transaction handler(103). The authorization message can be used to communicate the rewardsqualified for by the user (101) in response to the current transaction,the status and/or balance of rewards in a loyalty program, etc. Examplesand details related to the authorization process in one embodiment areprovided in U.S. Pat. App. Pub. No. 2007/0100691, entitled “Method andSystem for Conducting Promotional Programs,” the disclosure of which ishereby incorporated herein by reference.

In one embodiment, when the user (101) is conducting a transaction witha first merchant via the transaction handler (103), the transactionhandler (103) may determine whether the characteristics of thetransaction satisfy the conditions specified for an announcement, suchas an advertisement, offer or coupon, from a second merchant. If theconditions are satisfied, the transaction handler (103) provides theannouncement to the user (101). In one embodiment, the transactionhandler (103) may auction the opportunity to provide the announcementsto a set of merchants. Examples and details related to the delivery ofsuch announcements in one embodiment are provided in U.S. Pat. App. Pub.No. 2010/0274625, entitled “Targeting Merchant Announcements Triggeredby Consumer Activity Relative to a Surrogate Merchant,” the disclosureof which is hereby incorporated herein by reference.

Details about delivering advertisements at a point of interaction thatis associated with user transaction interactions in one embodiment areprovided in U.S. Pat. App. Pub. No. 2011/0087550, entitled “Systems andMethods to Deliver Targeted Advertisements to Audience,” the disclosureof which is hereby incorporated herein by reference.

On Third Party Site

In a further example, the user (101) may visit a third party website,which is the point of interaction (107) in FIG. 1. The third partywebsite may be a web search engine, a news website, a blog, a socialnetwork site, etc. The behavior of the user (101) at the third partywebsite may be tracked via a browser cookie, which uses a storage spaceof the browser to store information about the user (101) at the thirdparty website. Alternatively, or in combination, the third party websiteuses the server logs to track the activities of the user (101). In oneembodiment, the third party website may allow an advertisement networkto present advertisements on portions of the web pages. Theadvertisement network tracks the user's behavior using its server logsand/or browser cookies. For example, the advertisement network may use abrowser cookie to identify a particular user across multiple websites.Based on the referral uniform resource locators (URL) that cause theadvertisement network to load advertisements in various web pages, theadvertisement network can determine the online behavior of the user(101) via analyzing the web pages that the user (101) has visited. Basedon the tracked online activities of the user (101), the user data (125)that characterizes the user (101) can be formed to query the profileselector (129) for a user specific profile (131).

In one embodiment, the cookie identity of the user (101) as trackedusing the cookie can be correlated to an account of the user (101), thefamily of the user (101), the company of the user (101), or other groupsthat include the user (101) as a member. Thus, the cookie identity canbe used as the user data (125) to obtain the user specific profile(131). For example, when the user (101) makes an online purchase from aweb page that contains an advertisement that is tracked with the cookieidentity, the cookie identity can be correlated to the onlinetransaction and thus to the account of the user (101). For example, whenthe user (101) visits a web page after authentication of the user (101),and the web page includes an advertisement from the advertisementnetwork, the cookie identity can be correlated to the authenticatedidentity of the user (101). For example, when the user (101) signs in toa web portal (e.g., 143) of the transaction handler (103) to access theaccount of the user (101), the cookie identity used by the advertisementnetwork on the web portal (e.g., 143) can be correlated to the accountof the user (101).

Other online tracking techniques can also be used to correlate thecookie identity of the user (101) with an identifier of the user (101)known by the profile selector (129), such as a GUID, PAN, accountnumber, customer number, social security number, etc. Subsequently, thecookie identity can be used to select the user specific profile (131).

Multiple Communications

In one embodiment, the entity operating the transaction handler (103)may provide intelligence for providing multiple communications regardingan advertisement. The multiple communications may be directed to two ormore points of interaction with the user (101).

For example, after the user (101) is provided with an advertisement viathe transaction terminal (105), reminders or revisions to theadvertisements can be sent to the user (101) via a separate point ofinteraction (107), such as a mobile phone, email, text message, etc. Forexample, the advertisement may include a coupon to offer the user (101)a benefit contingent upon a purchase. If the correlator (117) determinesthat the coupon has not been redeemed, the correlator (117) may send amessage to the mobile phone of the user (101) to remind the user (101)about the offer, and/or revise the offer.

Examples of multiple communications related to an offer in oneembodiment are provided in U.S. Pat. App. Pub. No. 2011/0022424,entitled “Successive Offer Communications with an Offer Recipient,” thedisclosure of which is hereby incorporated herein by reference.

Auction Engine

In one embodiment, the transaction handler (103) provides a portal(e.g., 143) to allow various clients to place bids according to clusters(e.g., to target entities in the clusters for marketing, monitoring,researching, etc.)

For example, cardholders may register in a program to receive offers,such as promotions, discounts, sweepstakes, reward points, direct mailcoupons, email coupons, etc. The cardholders may register with issuers,or with the portal (143) of the transaction handler (103). Based on thetransaction data (109) or transaction records (301) and/or theregistration data, the profile generator (121) is to identify theclusters of cardholders and the values representing the affinity of thecardholders to the clusters. Various entities may place bids accordingto the clusters and/or the values to gain access to the cardholders,such as the user (101). For example, an issuer may bid on access tooffers; an acquirer and/or a merchant may bid on customer segments. Anauction engine receives the bids and awards segments and offers based onthe received bids. Thus, customers can get great deals; and merchantscan get customer traffic and thus sales.

Some techniques to identify a segment of users (101) for marketing areprovided in U.S. Pat. App. Pub. No. 2009/0222323, entitled “OpportunitySegmentation,” U.S. Pat. App. Pub. No. 2009/0271305, entitled “PaymentPortfolio Optimization,” and U.S. Pat. App. Pub. No. 2009/0271327,entitled “Payment Portfolio Optimization,” the disclosures of whichapplications are hereby incorporated herein by reference.

Social Network Validation

In one embodiment, the transaction data (109) is combined with socialnetwork data and/or search engine data to provide benefits (e.g.,coupons) to a consumer. For example, a data exchange apparatus mayidentify cluster data based upon consumer search engine data, socialnetwork data, and payment transaction data to identify like groups ofindividuals who would respond favorably to particular types of benefitssuch as coupons and statement credits. Advertisement campaigns may beformulated to target the cluster of consumers or cardholders.

In one embodiment, search engine data is combined with social networkdata and/or the transaction data (109) to evaluate the effectiveness ofthe advertisements and/or conversion pattern of the advertisements. Forexample, after a search engine displays advertisements about flat paneltelevisions to a consumer, a social network that is used by a consumermay provide information about a related purchase made by the consumer.For example, the blog of the consumer, and/or the transaction data(109), may indicate that the flat panel television purchased by theconsumer is from company B. Thus, the search engine data, the socialnetwork data and/or the transaction data (109) can be combined tocorrelate advertisements to purchases resulting from the advertisementsand to determine the conversion pattern of the advertisement presentedto the consumer. Adjustments to advertisements (e.g., placement,appearance, etc.) can be made to improve the effectiveness of theadvertisements and thus increase sales.

Loyalty Program

In one embodiment, the transaction handler (103) is to host loyaltyprograms on behalf of various entities, such as merchants, retailers,service providers, issuers, etc. For example, in one embodiment, theportal (143) of the transaction handler (103) is to provide a userinterface to present the loyalty programs and allow a user (e.g., 101)to enroll in one or more loyalty programs selected via the userinterface.

In one embodiment, the user (101) is to identify himself or herself viaan account identifier such as the account information (142) or theaccount number (302). After the user (101) accepts the terms andconditions for enrolling in a loyalty program, the account identifier ofthe user (101) is associated with the loyalty program in the datawarehouse (149) to indicate the membership of the user (101) in theloyalty program.

In one embodiment, the user (101) may have multiple accounts. After theuser (101) enrolls in the loyalty programs, the portal (143)automatically registers the account identifiers of the accounts of theuser (101) with the loyalty program. Thus, the user (101) can use any ofthe multiple accounts to access the benefits of the loyalty program.

In one embodiment, the user (101) may also enroll in a loyalty programindirectly using the portal (143). For example, the user (101) is toenroll in the loyalty program of a merchant through the merchant. Themerchant is to provide the enrollment data to the portal (143),identifying the user (101) and/or the account identifier of the user(101) and identifying the loyalty program. For example, the merchant mayenroll the user (101) via charging the user (101) a fee using theaccount identified by the account identifier, via a website taking theenrollment data, or via a registration form that records the enrollmentdata.

In one embodiment, the portal (143) also provides a user interface tothe loyalty program sponsor, such as a merchant, to administer the rulesof the loyalty program and/or access data stored under the loyaltyprograms, such as membership information, benefits provided to members,purchase details of members, etc.

In one embodiment, a loyalty program is provided by multiple entities,each having a different role. For example, one or more entities, such asan issuer, are to specify the rules of the loyalty program; and one ormore entities, such as merchants and retailers, are to provide funds forthe benefits of the loyalty program.

In one embodiment, the entity operating the transaction handler (103)may also provide funds to sponsor a loyalty program and/or specify rulesfor the loyalty program.

In one embodiment, the transaction handler (103) uses the account data(111) to store information for third party loyalty programs. Thetransaction handler (103) processes payment transactions made viafinancial transaction cards, such as credit cards, debit cards, bankingcards, etc.; and the financial transaction cards can be used as loyaltycards for the respective third party loyalty programs.

Since the third party loyalty programs are hosted on the transactionhandler (103), the consumers do not have to carry multiple, separateloyalty cards (e.g., one for each merchant that offers a loyaltyprogram); and the merchants do not have to incur a large setup andinvestment fee to establish the loyalty program.

The loyalty programs hosted on the transaction handler (103) can provideflexible awards for consumers, retailers, manufacturers, issuers, andother types of business entities involved in the loyalty programs. Theintegration of the loyalty programs into the accounts of the customerson the transaction handler (103) allows new offerings, such as merchantcross-offerings or bundling of loyalty offerings.

In one embodiment, an entity operating the transaction handler (103)hosts loyalty programs for third parties using the account data (111) ofthe users (e.g., 101). A third party, such as a merchant, retailer,manufacturer, issuer or other entity that is interested in promotingcertain activities and/or behaviors, may offer loyalty rewards onexisting accounts of consumers. The incentives delivered by the loyaltyprograms can drive behavior changes without the hassle of loyalty cardcreation. In one embodiment, the loyalty programs hosted via theaccounts of the users (e.g., 101) of the transaction handler (103) allowthe consumers to carry fewer cards and may provide more data to themerchants than traditional loyalty programs.

In one embodiment, the third party may use the transaction data (109)and/or transaction profiles (e.g., 127 or 341) to selectively offermemberships to the users (e.g., 101). For example, in one embodiment,the portal (143) is to provide a user interface for the third party tospecify eligibility requirements for a loyalty program via conditionsformulated based on transaction data (109) and/or certain values of thetransaction profiles (e.g., 127 or 341). In one embodiment, themembership offer is to be provided to the eligible users (e.g., 101) viathe portal (143), the transaction handler (103) and/or other mediachannels, such as the media controller (115).

For example, the portal (143) may provide the membership offer via a webpage, a text message, or an email to the eligible users (e.g., 101). Forexample, the transaction handler (103) may provide the membership offeron a transaction receipt. For example, the membership offer may beprovided via a media partner, such as a search engine, a socialnetworking site, etc.

In one embodiment, the eligible user (101) is to accept the membershipoffer via the portal (143), or via the transaction handler (103) (e.g.,via a transaction identifying the loyalty program, the accountidentifier, and/or the membership offer).

The loyalty programs integrated with the accounts of the users (e.g.,101) of the transaction handler (103) can provide tools to enable nimbleprograms that are better aligned for driving changes in consumerbehaviors across transaction channels (e.g., online, offline, via mobiledevices). The loyalty programs can be ongoing programs that accumulatebenefits for customers (e.g., points, miles, cash back), and/or programsthat provide one time benefits or limited time benefits (e.g., rewards,discounts, incentives).

FIG. 8 shows the structure of account data (111) for providing loyaltyprograms according to one embodiment. In FIG. 8, data related to a thirdparty loyalty program may include an identifier of the loyalty benefitofferor (183) that is linked to a set of loyalty program rules (185) andthe loyalty record (187) for the loyalty program activities of theaccount identifier (181). In one embodiment, at least part of the datarelated to the third party loyalty program is stored under the accountidentifier (181) of the user (101), such as the loyalty record (187).

FIG. 8 illustrates the data related to one third party loyalty programof a loyalty benefit offeror (183). In one embodiment, the accountidentifier (181) may be linked to multiple loyalty benefit offerors(e.g., 183), corresponding to different third party loyalty programs.

In one embodiment, a loyalty benefit offeror (183) represents a distinctloyalty program. The loyalty program may be provided by one entity, orbe provided collaboratively by multiple entities, such as issuers,merchants, retailers, service providers, etc.

In one embodiment, a third party loyalty program of the loyalty benefitofferor (183) provides the user (101), identified by the accountidentifier (181), with benefits, such as discounts, rewards, incentives,cash back, gifts, coupons, and/or privileges.

In one embodiment, the association between the account identifier (181)and the loyalty benefit offeror (183) in the account data (111)indicates that the user (101) having the account identifier (181) is amember of the loyalty program. Thus, the user (101) may use the accountidentifier (181) to access privileges afforded to the members of theloyalty program, such as rights to access a member only area, facility,store, product or service, discounts extended only to members, oropportunities to participate in certain events, buy certain items, orreceive certain services reserved for members.

In one embodiment, it is not necessary to make a purchase to use theprivileges. The user (101) may enjoy the privileges based on the statusof being a member of the loyalty program. The user (101) may use theaccount identifier (181) to show the status of being a member of theloyalty program.

For example, the user (101) may provide the account identifier (181)(e.g., the account number of a credit card) to the transaction terminal(105) to initiate an authorization process for a special transactionwhich is designed to check the member status of the user (101), in amanner similar to using the account identifier (181) to initiate anauthorization process for a payment transaction. The special transactionis designed to verify the member status of the user (101) via checkingwhether the account data (111) is associated with the loyalty benefitofferor (183). If the account identifier (181) is associated with thecorresponding loyalty benefit offeror (183), the transaction handler(103) provides an approval indication in the authorization process toindicate that the user (101) is a member of the loyalty program. Theapproval indication can be used as a form of identification to allow theuser (101) to access member privileges, such as rights to accessservices, products, opportunities, facilities, discounts, permissions,etc., which are reserved for members.

In one embodiment, when the account identifier (181) is used to identifythe user (101) as a member to access member privileges, the transactionhandler (103) stores information about the access of the correspondingmember privilege in loyalty record (187). The profile generator (121)may use the information accumulated in the loyalty record (187) toenhance transaction profiles (127) and provide the user (101) withpersonalized/targeted advertisements, with or without further offers ofbenefit (e.g., discounts, incentives, rebates, cash back, rewards,etc.).

In one embodiment, the association of the account identifier (181) andthe loyalty benefit offeror (183) also allows the loyalty benefitofferor (183) to access at least a portion of the account data (111)relevant to the loyalty program, such as the loyalty record (187) andcertain information about the user (101), such as name, address, andother demographic data.

In one embodiment, the loyalty program allows the user (101) toaccumulate benefits according to loyalty program rules (185), such asreward points, cash back, levels of discounts, etc. For example, theuser (101) may accumulate reward points for transactions that satisfythe loyalty program rules (185); and the user (101) may redeem thereward points for cash, gifts, discounts, etc. In one embodiment, theloyalty record (187) stores the accumulated benefits; and thetransaction handler (103) updates the loyalty record (187) associatedwith the loyalty benefit offeror (183) and the account identifier (181),when events that satisfy the loyalty program rules (185) occur.

In one embodiment, the accumulated benefits as indicated in the loyaltyrecord (187) can be redeemed when the account identifier (181) is usedto perform a payment transaction, when the payment transaction satisfiesthe loyalty program rules (185). For example, the user (101) may redeema number of points to offset or reduce an amount of a purchase price.

In one embodiment, the transaction handler (103) is to provide thebenefits of the loyalty program via statement credits. When thetransaction under the loyalty program is settled, the transactionhandler (103) is to compute the benefits resulting from the transactionand communicate with the issuer processor (145) and/or the acquirerprocessor (147) to provide corresponding statement credits according tothe computed amount of benefits. In one embodiment, when the loyaltyprogram is not sponsored by the merchant to whom the paymentcorresponding to the transaction is made, the transaction handler (103)is to initiate a transaction to settle the cost for providing thebenefit via the statement credits. For example, the transaction handler(103) is to charge an account of the sponsor of a loyalty program forthe amount of statement credits provided to the user (101) under theloyalty program.

In one embodiment, when the user (101) uses the account identifier (181)to make purchases as a member, the merchant may further provideinformation about the purchases; and the transaction handler (103) canstore the information about the purchases as part of the loyalty record(187). The information about the purchases may identify specific itemsor services purchased by the member. For example, the merchant mayprovide the transaction handler (103) with purchase details atstock-keeping unit (SKU) level, which are then stored as part of theloyalty record (187). The loyalty benefit offeror (183) may use thepurchase details to study the purchase behavior of the user (101); andthe profile generator (121) may use the SKU level purchase details toenhance the transaction profiles (127).

In one embodiment, the SKU level purchase details are requested from themerchants or retailers via authorization responses (e.g., as illustratedin FIG. 9 and discussed in the section entitled “PURCHASE DETAILS”),when the account (146) of the user (101) is enrolled in a loyaltyprogram that allows the transaction handler (103) (and/or the issuerprocessor (145)) to collect the purchase details.

In one embodiment, the profile generator (121) may generate transactionprofiles (127) based on the loyalty record (187) and provide thetransaction profiles (127) to the loyalty benefit offeror (183) (orother entities when permitted).

In one embodiment, the loyalty benefit offeror (183) may use thetransaction profiles (e.g., 127 or 131) to select candidates formembership offering. For example, the loyalty program rules (185) mayinclude one or more criteria that can be used to identify whichcustomers are eligible for the loyalty program. The transaction handler(103) may be configured to automatically provide the qualified customerswith an offer of membership in the loyalty program when thecorresponding customers are performing transactions via the transactionhandler (103) and/or via points of interaction (107) accessible to theentity operating the transaction handler (103), such as ATMs, mobilephones, receipts, statements, websites, etc. The user (101) may acceptthe membership offer via responding to the advertisement. For example,the user (101) may load the membership into the account in the same wayas loading a coupon into the account of the user (101).

In one embodiment, the membership offer is provided as a coupon or isassociated with another offer of benefits, such as a discount, reward,etc. When the coupon or benefit is redeemed via the transaction handler(103), the account data (111) is updated to enroll the user (101) intothe corresponding loyalty program.

In one embodiment, a merchant may enroll a user (101) into a loyaltyprogram when the user (101) is making a purchase at the transactionterminal (105) of the merchant.

For example, when the user (101) is making a transaction at an ATM,performing a self-assisted check out on a POS terminal, or making apurchase transaction on a mobile phone or a computer, the user (101) maybe prompted to join a loyalty program, while the transaction is beingauthorized by the transaction handler (103). If the user (101) acceptsthe membership offer, the account data (111) is updated to have theaccount identifier (181) associated with the loyalty benefit offeror(183).

In one embodiment, the user (101) may be automatically enrolled in theloyalty program, when the profile of the user (101) satisfies a set ofconditions specified in the loyalty program rules (185). The user (101)may opt out of the loyalty program.

In one embodiment, the loyalty benefit offeror (183) may personalizeand/or target loyalty benefits based on the transaction profile (131)specific to or linked to the user (101). For example, the loyaltyprogram rules (185) may use the user specific profile (131) to selectgifts, rewards, or incentives for the user (101) (e.g., to redeembenefits, such as reward points, accumulated in the loyalty record(187)). The user specific profile (131) may be enhanced using theloyalty record (187), or generated based on the loyalty record (187).For example, the profile generator (121) may use a subset of transactiondata (109) associated with the loyalty record (187) to generate the userspecific profile (131), or provide more weight to the subset of thetransaction data (109) associated with the loyalty record (187) whilealso using other portions of the transaction data (109) in deriving theuser specific profile (131).

In one embodiment, the loyalty program may involve different entities.For example, a first merchant may offer rewards as discounts, or giftsfrom a second merchant that has a business relationship with the firstmerchant. For example, an entity may allow a user (101) to accumulateloyalty benefits (e.g., reward points) via purchase transactions at agroup of different merchants. For example, a group of merchants mayjointly offer a loyalty program, in which loyalty benefits (e.g., rewardpoints) can be accumulated from purchases at any of the merchants in thegroup and redeemable in purchases at any of the merchants.

In one embodiment, the information identifying the user (101) as amember of a loyalty program is stored on a server connected to thetransaction handler (103). Alternatively or in combination, theinformation identifying the user (101) as a member of a loyalty programcan also be stored in the account identification device (141), such as afinancial transaction card (e.g., in the chip, or in the magneticstrip).

In one embodiment, loyalty program offerors (e.g., merchants,manufacturers, issuers, retailers, clubs, organizations, etc.) cancompete with each other in making loyalty program related offers. Theoffers can be provided via the system illustrated in FIG. 1. Competitorsmay bid against each other for opportunities to present the offers. Forexample, loyalty program offerors may place bids on offers that arerelated to loyalty programs; and the advertisement selector (133) (e.g.,under the control of the entity operating the transaction handler (103),or a different entity) may prioritize the offers based on the bids. Whenthe offers are accepted or redeemed by the user (101), the loyaltyprogram offerors pay fees according to the corresponding bids. In oneembodiment, the loyalty program offerors may place an auto bid ormaximum bid, which specifies the upper limit of a bid; and the actualbid is determined to be the lowest possible bid that is larger than thebids of the competitors, without exceeding the upper limit.

In one embodiment, the offers related to the loyalty programs areprovided to the user (101) in response to the user (101) beingidentified by the user data (125). If the user specific profile (131)satisfies the conditions specified in the loyalty program rules (185),the offer from the loyalty benefit offeror (183) can be presented to theuser (101). When there are multiple offers from different offerors, theoffers can be prioritized according to the bids.

In one embodiment, the offerors can place bids based on thecharacteristics that can be used as the user data (125) to select theuser specific profile (131). In another embodiment, the bids can beplaced on a set of transaction profiles (127).

In one embodiment, the loyalty program based offers are provided to theuser (101) just in time when the user (101) can accept and redeem theoffers. For example, when the user (101) is making a payment for apurchase from a merchant, an offer to enroll in a loyalty programoffered by the merchant or related offerors can be presented to the user(101). If the user (101) accepts the offer, the user (101) is entitledto receive member discounts for the purchase.

For example, when the user (101) is making a payment for a purchase froma merchant, a reward offer can be provided to the user (101) based onloyalty program rules (185) and the loyalty record (187) associated withthe account identifier (181) of the user (101)(e.g., the reward pointsaccumulated in a loyalty program). Thus, the user effort for redeemingthe reward points can be reduced; and the user experience can beimproved.

Details about targeting advertisement in one embodiment are provided inthe section entitled “TARGETING ADVERTISEMENT.”

In one embodiment, a method to provide loyalty programs includes the useof a computing apparatus of a transaction handler (103). The computingapparatus processes a plurality of payment card transactions. After thecomputing apparatus receives a request to track transactions for aloyalty program, such as the loyalty program rules (185), the computingapparatus stores and updates loyalty program information in response totransactions occurring in the loyalty program. The computing apparatusprovides to a customer (e.g., 101) an offer of a benefit when thecustomer satisfies a condition defined in the loyalty program, such asthe loyalty program rules (185).

FIG. 10 shows a system to provide loyalty programs according to oneembodiment. In FIG. 10, the system includes the data warehouse (149)coupled with the transaction handler (103) and the portal (143).

In one embodiment, the data warehouse (149) stores data that representsloyalty programs (e.g., 201). In one embodiment, the loyalty program(201) includes data identifying the loyalty benefit offeror (183) andthe loyalty program rules (185).

In one embodiment, the loyalty program rules (185) include theconditions to offer benefits, such as discounts, reward points, cashback, gifts, etc. The portal (143) and/or the transaction handler (103)is to use the loyalty program rules (185) to determine the amount ofbenefit to which a member (e.g., 101) is entitled (e.g., for completinga transaction). In one embodiment, the loyalty program rules (185)include the eligibility requirements for membership in the loyaltyprogram (201). The portal (143) is to use the loyalty program rules(185) to determine whether a user (101) is eligible for the membershipin the loyalty program (201). In one embodiment, the loyalty programrules (185) include the conditions to offer membership; and the portal(143) and/or the transaction handler (103) is to use the loyalty programrules (185) to determine whether or not the provide a membership offerto a user (101) when the user (101) makes a payment transaction via thetransaction handler (103) (or when the user (101) visits the portal(143), or in response to other advertising opportunities).

In one embodiment, the loyalty program rules (185) specify conditionsbased on the transaction data (109) and/or the transaction profiles(127). For example, in one embodiment, the loyalty program rules (185)are to define the membership eligibility based on whether certain values(e.g., 342-347) in the aggregated spending profile (341) of the user(101) are above certain thresholds, within certain ranges, and/or equalto certain predetermined values. Such conditions identify a cluster,segment, or set of users (e.g., 101) based on the past spending behaviorof the users (e.g., 101). Details about the profile (e.g., 133 or 341)in one embodiment are provided in the section entitled “TRANSACTIONPROFILE” and the section entitled “AGGREGATED SPENDING PROFILE.”

In one embodiment, the portal (143) is to provide membership offers tothe point of interaction (107) of eligible users (e.g., 101). Details ofthe point of interaction (107) in one embodiment are provided in thesection entitled “POINT OF INTERACTION.”

In one embodiment, an advertisement selector (133) is used to identifythe membership offers; and the membership offers are provided inresponse to user data (125).

In one embodiment, the portal (143) is to receive enrollment data fromthe point of interaction (107) of eligible users (e.g., 101). The portal(143) provides a user interface to the member (e.g., 101) of the loyaltyprogram (201) to view information related to the loyalty program (201),such as accumulated benefits, history of transactions made under theloyalty program (201), etc.

In one embodiment, the portal (143) also allows the loyalty benefitofferors (183) to view the information related to the loyalty program(201) of the members of the loyalty program (201). In one embodiment,enrolling in the loyalty program (201) includes providing consent toallow the portal (143) to track the information related to the loyaltyprogram (201) and grant the loyalty benefit offerors (183) access to theinformation related to the loyalty program (201).

In one embodiment, the loyalty benefit offerors (183) are to use theportal (143) to determine whether a user (e.g., 101) in possession of anaccount identification device (141) identifying the account identifier(181) is a member of the loyalty program (201).

In one embodiment, enrolling in the loyalty program (201) includesproviding consent to allow the portal (143) to track purchase details(169) for purchases made from a set of merchants, which merchants may ormay not be the loyalty benefit offeror (183). When the transactionhandler (103) receives an authorization request (168) from thetransaction terminal (105) via the acquirer processor (147) of thecorresponding merchant, the transaction handler (103) is to use the datawarehouse (149) to determine whether or not to request transactiondetails from the merchant.

In one embodiment, if the account identifier (181) in the authorizationrequest from a merchant is associated with a loyalty program (e.g., 201)that requires the tracking of the purchase details (169) fortransactions performed at the merchant, the transaction handler (103)and/or the portal (143) is to request the purchase details (169).

For example, in one embodiment, the transaction handler (103) is toembed the request (139) for purchase details (169) in the authorizationresponse (138), as illustrated in FIG. 9.

In one embodiment, the transaction handler (103) is to use thecommunication link with the transaction terminal (105), through theacquirer processor (147), to communicate loyalty data (203). Forexample, in one embodiment, the transaction handler (103) is to providethe identification of the loyalty program (201) in the authorizationresponse (138) to indicate that the corresponding user (101) making thepurchase is a member of the loyalty program (201). For example, in oneembodiment, the transaction handler (103) is to receive the requestedpurchase details (169) from the transaction terminal (105), through theacquirer processor (147).

In one embodiment, the portal (143) is used to receive the purchasedetails (169) from the merchant operating the transaction terminal(105). In response to the request (139) embedded in the authorizationresponse (138), the merchant is to save the purchase details (169) in afile and transmit the file with purchase details of other transactionsto the portal (143) (e.g., at the time of submitting the transactionsfor settlement, or at a regular and/or predefined time interval).

In one embodiment, the portal (143) is used to receive the purchasedetails (169) to avoid slowing down the transaction handler (103). Inone embodiment, the portal (143) is further used to transmit the request(139) for purchase details (169).

In one embodiment, the purchase details (169) individually identify theitems purchased and their prices. In one embodiment, the purchasedetails (169) are used to determine the benefits to be awarded to theaccount identifier (181). For example, in some embodiments, certainpurchased items are eligible for benefits; and other purchased items arenot eligible for benefits. For example, in some embodiments, purchaseditems in some categories are eligible for more benefits (e.g., accordingto a first percentage number); and purchased items are other categorieseligible for less benefits (e.g., according to a second percentagenumber). In one embodiment, the purchase details (169) are not requiredto determine the benefits, such as when the benefits are based on thetotal transaction amount.

In one embodiment, the benefits are provided in the form of statementcredits. For example, in one embodiment, during the settlement of thetransaction, the transaction handler (103) is to communicate with theissuer processor (145) associated with the account identifier (181) andthe acquirer processor (147) is to modify the transaction to include thestatement credits, so that the user (101) receives the discount via thestatement credits and the merchant provides the benefit via the pricediscount. When the benefit is provided by a third party that is not themerchant involved in the transaction, the transaction handler (103) isto use the data about the loyalty benefit offeror (183) to settle thecost for providing the statement credits.

FIG. 11 shows a method to administrate a loyalty program according toone embodiment. In FIG. 11, a computing apparatus is configured toreceive (221), from a transaction terminal (105) via an acquirerprocessor (147), an authorization request (168) having an accountidentifier (181), contact (223) an issuer processor (145) to obtain aresponse to the authorization request (168) based on the accountidentifier (181), and determine (225) whether the account identifier(181) is enrolled in a loyalty program (201) relevant to theauthorization request (168). If it is determined (226) that the accountidentifier (181) is enrolled in one of the loyalty programs (e.g., 201)hosted on the computing apparatus, the computing apparatus is to add(227) a request (139) for purchase details (169) in an authorizationresponse (138). The computing apparatus is to transmit (229) theauthorization response (138) to the transaction terminal (105) via theacquirer processor (147). In one embodiment, the authorization response(138) includes an authorization code (137) to confirm the authorizationof the transaction; and the computing apparatus is to receive thetransaction details (169) from the merchant together with the request tosettle the transaction that was authorized by the authorization response(138). In one embodiment, the authorization code (137) is based on theresponse from the issuer processor (145) regarding the authorizationrequest (168).

In one embodiment, the request (139) for purchase details (169) isfurther in response to an approval decision made by the issuer processor(145) responding to the authorization request (168). If the issuerprocessor (145) does not approve the authorization request (168), thecomputing apparatus is not to request (139) the purchase details (169).

In one embodiment, the computing apparatus includes at least one of: thedata warehouse (149), the transaction handler (103), the portal (143),the profile generator (121), the advertisement selector (133), and themedia controller (115).

In one embodiment, if the authorization request (168) is for an accountidentifier (181) associated with a relevant loyalty program (201), thecomputing apparatus is to request the purchase details (169) of thepayment transaction associated with the authorization request (168) anddetermine benefits to be awarded to the customer according to theloyalty program (201).

In one embodiment, the benefits are determined based on the requestedpurchase details (169). The benefits may be discount, incentive, reward,gift, or cash back. In one embodiment, the computing apparatus is toaccumulate the benefits for the user (101) using the loyalty record(187) stored in the data warehouse (149).

In one embodiment, the computing apparatus is to provide the benefitsvia statement credits to the account identifier (181) via the issuerprocessor (145) during the settlement of the transaction that has beenauthorized via the authorization response (138). Alternatively, thecomputing apparatus may store data (e.g., loyalty record (187)) toaccumulate the benefits under the account identifier (181). Theaccumulated benefits can be provided to the account identifier (181) viastatement credits, cash back, or gifts, such as airline tickets.

In one embodiment, the computing apparatus hosts a plurality of loyaltyprograms (e.g., 201) on behalf of a plurality of different entities; andthe data (e.g., loyalty record (187)) to accumulate the benefits isstored in association with the loyalty program (201).

In one embodiment, the computing apparatus is to determine whether apurchase from the merchant is relevant to the loyalty program (201). Thecomputing apparatus is to skip requesting (139) the purchase details(169), if a purchase from the merchant is not relevant to the loyaltyprogram (201). For example, if the computing apparatus is to usepurchase details (169) to determine the benefits according to theloyalty program rules (185), or if the loyalty program rules (185)requires the computing apparatus to track the purchase details (169) fortransactions made with the merchant operating the transaction terminal(105), the purchase details (169) are relevant to the loyalty program(201).

In one embodiment, the computing apparatus is to use the response (138)to the authorization request (168) to provide the indication that thecustomer is enrolled in the loyalty program (201). Thus, for example,the merchant may provide certain benefits to the customer based on themembership in the loyalty program (201) without even requesting thecustomer to make a purchase.

In one embodiment, the computing apparatus is to receive an input fromthe customer to enroll in the loyalty program (201); the inputidentifies the account identifier (181); and the computing apparatus isto store data associating the account identifier (181) with the loyaltyprogram (201) to indicate the membership of the account identifier (181)in the loyalty program (201).

In one embodiment, the customer may choose to enroll in multiple loyaltyprograms (e.g., 201); and the computing apparatus is to store data toassociate the account identifier (181) of the customer with therespective loyalty programs (e.g., 201).

In one embodiment, the loyalty program (201) is sponsored by themerchant; and the computing apparatus is to store purchase details (169)under the loyalty program (201) on behalf of the merchant. The computingapparatus is to provide a user interface to allow the merchant to accessand mine the purchase details (169) of various members enrolled in theloyalty program (201) to study the purchase behaviors of the members.

In one embodiment, a system includes: a transaction handler (103) toprocess transactions; a portal (143) to receive from users enrollmentinput identifying account identifiers (e.g., 181) of the users (e.g.,101) and respective loyalty programs (e.g., 201) in which the accountidentifiers (e.g., 181) are enrolled; and a data warehouse (149) tostore data associating the account identifiers (e.g., 181) with therespective loyalty programs (e.g., 201).

In one embodiment, in response to an authorization request (168)received in the transaction handler (103) for a payment transactionidentifying a first account identifier (181), the system is to use thedata warehouse (149) to determine whether the first account identifier(181) is enrolled with a loyalty program (201); and if the first accountidentifier is enrolled with a first loyalty program (201), the system isto use the transaction handler (103) to request purchase details (169)from the merchant via a response (138) to the authorization request(168), receive and store the purchase details (169) in the datawarehouse (149), and determine benefits to be awarded to the user (101)of the first account identifier (181), according to the rules (185) ofthe first loyalty program (201) and the purchase details (169).

In one embodiment, each of the transactions processed by the transactionhandler (103) is to make a payment from an issuer processor (145) to anacquirer processor (147) via the transaction handler (103) in responseto an account identifier (181) of a customer, as issued by an issuer,being submitted by a merchant to an acquirer; the issuer is to use theissuer processor to make the payment on behalf of the customer; and theacquirer is to use the acquirer processor to receive the payment onbehalf of the merchant. Details about the transaction handler (103) andthe portal (143) in one embodiment are provided in the section entitled“TRANSACTION DATA BASED PORTAL.”

In one embodiment, the portal (143) is to receive the purchase details(169). For example, in one embodiment, the portal (143) is to receivethe purchase details (169) in a file together with purchase details offurther transactions that have been requested within a period of time.In one embodiment, the purchase details (169) are received with aseparate request to settle the payment transaction.

Details about the system in one embodiment are provided in the sectionsentitled “SYSTEM,” “CENTRALIZED DATA WAREHOUSE” and “HARDWARE.”

Examples of loyalty programs offered through collaboration betweencollaborative constituents in a payment processing system, including thetransaction handler (103) in one embodiment are provided in U.S. Pat.App. Pub. No. 2008/0059302, entitled “Loyalty Program Service,” U.S.Pat. App. Pub. No. 2008/0059306, entitled “Loyalty Program IncentiveDetermination,” and U.S. Pat. App. Pub. No. 2008/0059307, entitled“Loyalty Program Parameter Collaboration,” the disclosures of whichapplications are hereby incorporated herein by reference.

Examples of processing the redemption of accumulated loyalty benefitsvia the transaction handler (103) in one embodiment are provided in U.S.Pat. App. Pub. No. 2008/0059303, entitled “Transaction Evaluation forProviding Rewards,” the disclosure of which is hereby incorporatedherein by reference.

In one embodiment, the incentive, reward, or benefit provided in theloyalty program (201) is based on the presence of correlated relatedtransactions. For example, in one embodiment, an incentive is providedif a financial payment card is used in a reservation system to make areservation and the financial payment card is subsequently used to payfor the reserved good or service. Further details and examples of oneembodiment are provided in U.S. Pat. App. Pub. No. 2008/0071587,entitled “Incentive Wireless Communication Reservation,” the disclosureof which is hereby incorporated herein by reference.

In one embodiment, the transaction handler (103) provides centralizedloyalty program management, reporting and membership services. In oneembodiment, membership data is downloaded from the transaction handler(103) to acceptance point devices, such as the transaction terminal(105). In one embodiment, loyalty transactions are reported from theacceptance point devices to the transaction handler (103); and the dataindicating the loyalty points, rewards, benefits, etc. are stored on theaccount identification device (141). Further details and examples of oneembodiment are provided in U.S. Pat. App. Pub. No. 2004/0054581,entitled “Network Centric Loyalty System,” the disclosure of which ishereby incorporated herein by reference.

In one embodiment, the portal (143) of the transaction handler (103) isused to manage reward or loyalty programs for entities such as issuers,merchants, etc. The cardholders, such as the user (101), are rewardedwith offers/benefits from merchants. The portal (143) and/or thetransaction handler (103) track the transaction records for themerchants for the reward or loyalty programs. Further details andexamples of one embodiment are provided in U.S. Pat. App. Pub. No.2008/0195473, entitled “Reward Program Manager,” the disclosure of whichis hereby incorporated herein by reference.

In one embodiment, a loyalty program includes multiple entitiesproviding access to detailed transaction data, which allows theflexibility for the customization of the loyalty program (201). Forexample, issuers or merchants may sponsor the loyalty program (201) toprovide rewards; and the portal (143) and/or the transaction handler(103) stores the loyalty currency in the data warehouse (149). Furtherdetails and examples of one embodiment are provided in U.S. Pat. App.Pub. No. 2009/0030793, entitled “Multi-Vendor Multi-Loyalty CurrencyProgram,” the disclosure of which is hereby incorporated herein byreference.

In one embodiment, an incentive program is created on the portal (143)of the transaction handler (103). The portal (143) collects offers froma plurality of merchants and stores the offers in the data warehouse(149). The offers may have associated criteria for their distributions.The portal (143) and/or the transaction handler (103) may recommendoffers based on the transaction data (109). In one embodiment, thetransaction handler (103) automatically applies the benefits of theoffers during the processing of the transactions when the transactionssatisfy the conditions associated with the offers. In one embodiment,the transaction handler (103) communicates with transaction terminals(e.g., 105) to set up, customize, and/or update offers based on marketfocus, product categories, service categories, targeted consumerdemographics, etc. Further details and examples of one embodiment areprovided in U.S. Pat. App. Pub. No. 2010/0049620, entitled “MerchantDevice Support of an Integrated Offer Network,” the disclosure of whichis hereby incorporated herein by reference.

In one embodiment, the transaction handler (103) is configured toprovide offers from merchants to the user (101) via the payment system,making accessing and redeeming the offers convenient for the user (101).The offers may be triggered by and/or tailored to a previoustransaction, and may be valid only for a limited period of time startingfrom the date of the previous transaction. If the transaction handler(103) determines that a subsequent transaction processed by thetransaction handler (103) meets the conditions for the redemption of anoffer, the transaction handler (103) may credit the consumer account(146) for the redemption of the offer and/or provide a notificationmessage to the user (101). Further details and examples of oneembodiment are provided in U.S. Pat. App. Pub. No. 2010/0114686,entitled “Real-Time Statement Credits and Notifications,” the disclosureof which is hereby incorporated herein by reference.

Details on loyalty programs in one embodiment are provided in U.S. Pat.App. Pub. No. 2011/0087530, entitled “Systems and Methods to ProvideLoyalty Programs,” the disclosure of which is hereby incorporated hereinby reference.

SKU

In one embodiment, merchants generate stock-keeping unit (SKU) or otherspecific information that identifies the particular goods and servicespurchased by the user (101) or customer. The SKU information may beprovided to the operator of the transaction handler (103) that processedthe purchases. The operator of the transaction handler (103) may storethe SKU information as part of transaction data (109), and reflect theSKU information for a particular transaction in a transaction profile(127 or 131) associated with the person involved in the transaction.

When a user (101) shops at a traditional retail store or browses awebsite of an online merchant, an SKU-level profile associatedspecifically with the user (101) may be provided to select anadvertisement appropriately targeted to the user (101) (e.g., via mobilephones, POS terminals, web browsers, etc.). The SKU-level profile forthe user (101) may include an identification of the goods and serviceshistorically purchased by the user (101). In addition, the SKU-levelprofile for the user (101) may identify goods and services that the user(101) may purchase in the future. The identification may be based onhistorical purchases reflected in SKU-level profiles of otherindividuals or groups that are determined to be similar to the user(101). Accordingly, the return on investment for advertisers andmerchants can be greatly improved.

In one embodiment, the user specific profile (131) is an aggregatedspending profile (341) that is generated using the SKU-levelinformation. For example, in one embodiment, the factor values (344)correspond to factor definitions (331) that are generated based onaggregating spending in different categories of products and/orservices. A typical merchant offers products and/or services in manydifferent categories.

In one embodiment, the user (101) may enter into transactions withvarious online and “brick and mortar” merchants. The transactions mayinvolve the purchase of various goods and services. The goods andservices may be identified by SKU numbers or other information thatspecifically identifies the goods and services purchased by the user(101).

In one embodiment, the merchant may provide the SKU informationregarding the goods and services purchased by the user (101) (e.g.,purchase details at SKU level) to the operator of the transactionhandler (103). In one embodiment, the SKU information may be provided tothe operator of the transaction handler (103) in connection with aloyalty program, as described in more detail below. The SKU informationmay be stored as part of the transaction data (109) and associated withthe user (101). In one embodiment, the SKU information for itemspurchased in transactions facilitated by the operator of the transactionhandler (103) may be stored as transaction data (109) and associatedwith its associated purchaser.

In one embodiment, the SKU level purchase details are requested from themerchants or retailers via authorization responses (e.g., as illustratedin FIG. 9), when the account (146) of the user (101) is enrolled in aprogram that allows the transaction handler (103) (and/or the issuerprocessor (145)) to collect the purchase details.

In one embodiment, based on the SKU information and perhaps othertransaction data, the profile generator (121) may create an SKU-leveltransaction profile for the user (101). In one embodiment, based on theSKU information associated with the transactions for each personentering into transactions with the operator of the transaction handler(103), the profile generator (121) may create an SKU-level transactionprofile for each person.

In one embodiment, the SKU information associated with a group ofpurchasers may be aggregated to create an SKU-level transaction profilethat is descriptive of the group. The group may be defined based on oneor a variety of considerations. For example, the group may be defined bycommon demographic features of its members. As another example, thegroup may be defined by common purchasing patterns of its members.

In one embodiment, the user (101) may later consider the purchase ofadditional goods and services. The user (101) may shop at a traditionalretailer or an online retailer. With respect to an online retailer, forexample, the user (101) may browse the website of an online retailer,publisher, or merchant. The user (101) may be associated with a browsercookie to, for example, identify the user (101) and track the browsingbehavior of the user (101).

In one embodiment, the retailer may provide the browser cookieassociated with the user (101) to the operator of the transactionhandler (103). Based on the browser cookie, the operator of thetransaction handler (103) may associate the browser cookie with apersonal account number of the user (101). The association may beperformed by the operator of the transaction handler (103) or anotherentity in a variety of manners such as, for example, using a look uptable.

Based on the personal account number, the profile selector (129) mayselect a user specific profile (131) that constitutes the SKU-levelprofile associated specifically with the user (101). The SKU-levelprofile may reflect the individual, prior purchases of the user (101)specifically, and/or the types of goods and services that the user (101)has purchased.

The SKU-level profile for the user (101) may also includeidentifications of goods and services the user (101) may purchase in thefuture. In one embodiment, the identifications may be used for theselection of advertisements for goods and services that may be ofinterest to the user (101). In one embodiment, the identifications forthe user (101) may be based on the SKU-level information associated withhistorical purchases of the user (101). In one embodiment, theidentifications for the user (101) may be additionally or alternativelybased on transaction profiles associated with others. Therecommendations may be determined by predictive association and otheranalytical techniques.

For example, the identifications for the user (101) may be based on thetransaction profile of another person. The profile selector (129) mayapply predetermined criteria to identify another person who, to apredetermined degree, is deemed sufficiently similar to the user (101).The identification of the other person may be based on a variety offactors including, for example, demographic similarity and/or purchasingpattern similarity between the user (101) and the other person. As oneexample, the common purchase of identical items or related items by theuser (101) and the other person may result in an association between theuser (101) and the other person, and a resulting determination that theuser (101) and the other person are similar. Once the other person isidentified, the transaction profile constituting the SKU-level profilefor the other person may be analyzed. Through predictive association andother modeling and analytical techniques, the historical purchasesreflected in the SKU-level profile for the other person may be employedto predict the future purchases of the user (101).

As another example, the identifications of the user (101) may be basedon the transaction profiles of a group of persons. The profile selector(129) may apply predetermined criteria to identify a multitude ofpersons who, to a predetermined degree, are deemed sufficiently similarto the user (101). The identification of the other persons may be basedon a variety of factors including, for example, demographic similarityand/or purchasing pattern similarity between the user (101) and theother persons. Once the group constituting the other persons isidentified, the transaction profile constituting the SKU-level profilefor the group may be analyzed. Through predictive association and othermodeling and analytical techniques, the historical purchases reflectedin the SKU-level profile for the group may be employed to predict thefuture purchases of the user (101).

The SKU-level profile of the user (101) may be provided to select anadvertisement that is appropriately targeted. Because the SKU-levelprofile of the user (101) may include identifications of the goods andservices that the user (101) may be likely to buy, advertisementscorresponding to the identified goods and services may be presented tothe user (101). In this way, targeted advertising for the user (101) maybe optimized. Further, advertisers and publishers of advertisements mayimprove their return on investment, and may improve their ability tocross-sell goods and services.

In one embodiment, SKU-level profiles of others who are identified to besimilar to the user (101) may be used to identify a user (101) who mayexhibit a high propensity to purchase goods and services. For example,if the SKU-level profiles of others reflect a quantity or frequency ofpurchase that is determined to satisfy a threshold, then the user (101)may also be classified or predicted to exhibit a high propensity topurchase. Accordingly, the type and frequency of advertisements thataccount for such propensity may be appropriately tailored for the user(101).

In one embodiment, the SKU-level profile of the user (101) may reflecttransactions with a particular merchant or merchants. The SKU-levelprofile of the user (101) may be provided to a business that isconsidered a peer with or similar to the particular merchant ormerchants. For example, a merchant may be considered a peer of thebusiness because the merchant offers goods and services that are similarto or related to those of the business. The SKU-level profile reflectingtransactions with peer merchants may be used by the business to betterpredict the purchasing behavior of the user (101) and to optimize thepresentation of targeted advertisements to the user (101).

Details on SKU-level profile in one embodiment are provided in U.S. Pat.App. Pub. No. 2011/0093335, entitled “Systems and Methods forAdvertising Services Based on an SKU-Level Profile,” the disclosure ofwhich is hereby incorporated herein by reference.

Purchase Details

In one embodiment, the transaction handler (103) is configured toselectively request purchase details via authorization responses. Whenthe transaction handler (103) (and/or the issuer processor (145)) needspurchase details, such as identification of specific items purchasedand/or their prices, the authorization responses transmitted from thetransaction handler (103) is to include an indicator to request for thepurchase details for the transaction that is being authorized. Themerchants are to determine whether or not to submit purchase detailsbased on whether or not there is a demand indicated in the authorizationresponses from the transaction handler (103).

For example, in one embodiment, the transaction handler (103) isconfigured for the redemption of manufacturer coupons via statementcredits. Manufacturers may provide users (e.g., 101) with promotionaloffers, such as coupons for rebate, discounts, cash back, reward points,gifts, etc. The offers can be provided to users (e.g., 101) via variouschannels, such as websites, newspapers, direct mail, targetedadvertisements (e.g., 119), loyalty programs, etc.

In one embodiment, when the user (101) has one or more offers pendingunder the consumer account (146) and uses the consumer account (146) topay for purchases made from a retailer that supports the redemption ofthe offers, the transaction handler (103) is to use authorizationresponses to request purchase details, match offer details against theitems shown to be purchased in the purchase details to identify aredeemable offer, and manage the funding for the fulfillment of theredeemable offer between the user (101) and the manufacturer that fundedthe corresponding offer. In one embodiment, the request for purchasedetails is provided in real time with the authorization message; and theexchange of the purchase details and matching may occur real-timeoutside the authorization process, or at the end of the day via a batchfile for multiple transactions.

In one embodiment, the offers are associated with the consumer account(146) of the user (101) to automate the processing of the redemption ofthe offers. If the user (101) makes a payment for a purchase using theconsumer account (146) of the user (101), the transaction handler (103)(and/or the issuer processor (145)) processes the payment transactionand automatically identifies the offers that are qualified forredemption in view of the purchase and provides the benefit of thequalified offers to the user (101). In one embodiment, the transactionhandler (103) (or the issuer processor (145)) is to detect theapplicable offer for redemption and provide the benefit of the redeemedoffer via statement credits, without having to request the user (101) toperform additional tasks.

In one embodiment, once the user (101) makes the required purchaseaccording to the requirement of the offer using the consumer account(146), the benefit of the offer is fulfilled via the transaction handler(103) (or the issuer processor (145)) without the user (101) having todo anything special at and/or after the time of checkout, other thanpaying with the consumer account (146) of the user (101), such as acredit card account, a debit card account, a loyalty card account, aprivate label card account, a coupon card account, or a prepaid cardaccount that is enrolled in the program for the automation of offerredemption.

In one embodiment, the redemption of an offer (e.g., a manufacturercoupon) requires the purchase of a specific product or service. The user(101) is eligible for the benefit of the offer after the purchase of thespecific product or service is verified. In one embodiment, thetransaction handler (103) (or the issuer processor (145)) dynamicallyrequests the purchase details via authorization response to determinethe eligibility of a purchase for the redemption of such an offer.

In one embodiment, the methods to request purchase details on demand via(or in connection with) the authorization process are used in othersituations where the transaction level data is needed on a case-by-casebasis as determined by the transaction handler (103).

For example, in one embodiment, the transaction handler (103) and/or theissuer processor (145) determines that the user (101) has signed up toreceive purchase item detail electronically, the transaction handler(103) and/or the issuer processor (145) can make the request on demand;and the purchase details can be stored and later downloaded into apersonal finance software application or a business accounting softwareapplication.

For example, in one embodiment, the transaction handler (103) and/or theissuer processor (145) determines that the user (101) has signed up toautomate the process of reimbursements of health care items qualifiedunder certain health care accounts, such as a health savings account(HSA), a flexible spending arrangement (FSA), etc. In response to such adetermination, the transaction handler (103) and/or the issuer processor(145) requests the purchase details to automatically identify qualifiedhealth care item purchases, capture and reporting evidences showing thequalification, bookkeeping the receipts or equivalent information forsatisfy rules, regulations and laws reporting purposes (e.g., asrequired by Internal Revenue Service), and/or settle the reimbursementof the funds with the respective health care accounts.

FIG. 9 shows a system to obtain purchase details according to oneembodiment. In FIG. 9, when the user (101) uses the consumer account(146) to make a payment for a purchase, the transaction terminal (105)of the merchant or retailer sends an authorization request (168) to thetransaction handler (103). In response, an authorization response (138)is transmitted from the transaction handler (103) to the transactionterminal (105) to inform the merchant or retailer of the decision toapprove or reject the payment request, as decided by the issuerprocessor (145) and/or the transaction handler (103). The authorizationresponse (138) typically includes an authorization code (137) toidentify the transaction and/or to signal that the transaction isapproved.

In one embodiment, when the transaction is approved and there is a needfor purchase details (169), the transaction handler (103) (or the issuerprocessor (145)) is to provide an indicator of the request (139) forpurchase details in the authorization response (138). The optionalrequest (139) allows the transaction handler (103) (and/or the issuerprocessor (145)) to request purchase details (169) from the merchant orretailer on demand. When the request (139) for purchase details ispresent in the authorization response (138), the transaction terminal(105) is to provide the purchase details (169) associated with thepayment transaction to the transaction handler (103) directly orindirectly via the portal (143). When the request (139) is absent fromthe authorization response (138), the transaction terminal (105) doesnot have to provide the purchase details (169) for the paymenttransaction.

In one embodiment, when the transaction is approved but there is no needfor purchase details (169), the indicator for the request (139) forpurchase details is not set in the authorization response (138).

In one embodiment, prior to transmitting the authorization response(138), the transaction handler (103) (and/or the issuer processor (145))determines whether there is a need for transaction details. In oneembodiment, when there is no need for the purchase details (169) for apayment transaction, the request (139) for purchase details (169) is notprovided in the authorization response (138) for the paymenttransaction. When there is a need for the purchase details (169) for apayment transaction, the request (139) for purchase details is providedin the authorization response (138) for the payment transaction. Themerchants or retailers do not have to send detailed purchase data to thetransaction handler (103) when the authorization response message doesnot explicitly request detailed purchase data.

Thus, the transaction handler (103) (or the issuer processor (145)) doesnot have to require all merchants or retailers to send the detailedpurchase data (e.g., SKU level purchase details) for all paymenttransactions processed by the transaction handler (103) (or the issuerprocessor (145)).

For example, when the consumer account (146) of the user (103) hascollected a manufacturer coupon for a product or service that may besold by the merchant or retailer operating the transaction terminal(105), the transaction handler (103) is to request the purchase details(169) via the authorization response (138) in one embodiment. If thepurchase details (169) show that the conditions for the redemption ofthe manufacturer coupon are satisfied, the transaction handler (103) isto provide the benefit of the manufacturer coupon to the user (101) viacredits to the statement for the consumer account (146). This automationof the fulfillment of manufacturer coupon releases the merchant/retailerfrom the work and complexities in processing manufacturer offers andimproves user experiences. Further, retailers and manufacturers areprovided with a new consumer promotion distribution channel through thetransaction handler (103), which can target the offers based on thetransaction profiles (127) of the user (101) and/or the transaction data(109). In one embodiment, the transaction handler (103) can use theoffer for loyalty/reward programs.

In another example, if the user (101) is enrolled in a program torequest the transaction handler (103) to track and manage purchasedetails (169) for the user (103), the transaction handler (103) is torequest the transaction details (169) via the authorization response(138).

In one embodiment, a message for the authorization response (138) isconfigured to include a field to indicate whether purchase details arerequested for the transaction.

In one embodiment, the authorization response message includes a fieldto indicate whether the account (146) of the user (101) is a participantof a coupon redemption network. When the field indicates that theaccount (146) of the user (101) is a participant of a coupon redemptionnetwork, the merchant or retailer is to submit the purchase details(169) for the payment made using the account (146) of the user (101).

In one embodiment, when the request (139) for the purchase details (169)is present in the authorization response (138), the transaction terminal(105) of the merchant or retailer is to store the purchase details (169)with the authorization information provided in the authorizationresponse (138). When the transaction is submitted to the transactionhandler (103) for settlement, the purchase details (169) are alsosubmitted with the request for settlement.

In one embodiment, the purchase details (169) are transmitted to thetransaction handler (103) via a communication channel separate from thecommunication channel used for the authorization and/or settlementrequests for the transaction. For example, the merchant or the retailermay report the purchase details to the transaction handler (103) via aportal (143) of the transaction handler (103). In one embodiment, thereport includes an identification of the transaction (e.g., anauthorization code (137) for the payment transaction) and the purchasedetails (e.g., SKU number, Universal Product Code (UPC)).

In one embodiment, the portal (143) of the transaction handler (103) mayfurther communicate with the merchant or the retailer to reduce theamount of purchase detail data to be transmitted the transaction handler(103). For example, in one embodiment, the transaction handler (103)provides an indication of categories of services or products for whichthe purchase details (169) are requested; and the merchant or retaileris to report only the items that are in these categories. In oneembodiment, the portal (143) of the transaction handler (103) is to askthe merchant or the retailer to indicate whether the purchased itemsinclude a set of items required for the redemption of the offers.

In one embodiment, the merchant or retailer is to complete the purchasebased upon the indication of approval provided in the authorizationresponse (138). When the indicator (e.g., 139) is present in theauthorization response (138), the merchant (e.g. inventory managementsystem or the transaction terminal (105)) is to capture and retain thepurchase details (169) in an electronic data file. The purchase details(169) include the identification of the individual items purchased(e.g., SKU and/or UPC), their prices, and/or brief descriptions of theitems.

In one embodiment, the merchant or retailer is to send the transactionpurchase data file to the transaction handler (103) (or the issuerprocessor (145)) at the end of the day, or according to some otherprearranged schedule. In one embodiment, the data file for purchasedetails (169) is transmitted together with the request to settle thetransaction approved via the authorization response (138). In oneembodiment, the data file for purchase details (169) is transmittedseparately from the request to settle the transaction approved via theauthorization response (138).

Further details and examples of one embodiment of offer fulfillment areprovided in U.S. Pat. App. Pub. No. 2011/0288918, entitled “Systems andMethods for Redemption of Offers,” the disclosure of which is herebyincorporated herein by reference.

Travel

In one embodiment, the transaction handler (103) is configured to helphotel chains capture a share of the business traveler market by matchingcustomers with desired hotels, based on information and/or knowledgeabout who is staying in hotels and why. In one embodiment, theinformation and/or knowledge is generated from correlating transactiondata (109) related to travels, and announcements, reporting, ordiscussions of events that have impact on travels.

In one embodiment, the transaction handler (103) is configured toanalyze segments of customers and the types of merchants the customersof the segments like to frequent. The transaction handler (103) isconfigured to dynamically provide information about the customersegments, as well as other aspects of the customers, to the respectivemerchants in real time, or near real time, when opportunities toinfluence the customers and/or the merchants appear. Such informationcan be used by the merchants to provide offers, such as upgrades, VIPtreatment, etc., to improve customer loyalty and/or to attract newcustomers.

In one embodiment, an analytic tool allows individuals to set up alertsbased on specific events from significant global economic news, futuresshifts, business volume shifts (e.g., identified based on profileinformation provided by a hotel chain analyst), and real time changes inbuying patterns identified from the transaction data (109) generated bythe transaction handler (103). The analytic tool is configured to reportdynamically off the data warehouse (149) maintained at the transactionhandler (103), allowing merchants to view reports about what hashappened and what is happening in near real time by customer segment andmerchant peer group, and predict what is most likely to happen based onknown environmental data and airline, hotel and car data, which may beaccessed via commercial systems.

In one embodiment, the travel related merchants, such as hotel chains,airlines, etc., are charged a fee to access the centralized predictiveanalytics generated from the transaction data (109) and otherinformation related to various events that are relevant to the travelactivities. The centralized predictive analytics allow the merchants todesign advertisement campaigns and incentive, reward, or discountoffers.

In one embodiment, a merchant can opt into a program that allows themerchant to become a part of peer group reporting, provided in a waythat follows anti-trust guidelines and having the capability to identifypotential hotel, merchant and airline coalition partners and to identifykey customer segments across the coalition partners to boost theirbusiness in revenue and profit. The potential coalition partners can beidentified via analyzing the clustering of merchants based on thetransaction data (109).

In one embodiment, upon approval, consulting firms can access themerchant groups that opt in for a fee to analyze the merchants on behalfof the transaction handler (103), investors and/or the merchants. Theconsulting firms can be provided with event-based information and/or thecentralized predictive analytics to coach the merchants on drivingloyalty and customer transactions based on the business intelligenceserved up from the analytical tool.

In one embodiment, frequent travelers can sign up for a travel programto get VIP treatment at certain hotel chains (e.g., preferential roomupgrades, and specific offers tailored to their needs based on theirprofile and stay history preferences). The travelers may or may not berequired to pay a fee to sign up for the travel program. Based on opt inrules, the analytic tool is configured to provide integration capabilityto update third party databases (e.g., at Epsion and/or Acxiom) so thatthe hotel reservation and front desk systems can readily recognize thesetravelers for VIP treatment.

In one embodiment, the merchants can enroll in event-based marketingcampaigns to provide near real time offers via media channels accessibleto the transaction handler (103). Further details and examples aboutnear real time offers via media channels accessible to the transactionhandler (103) can be found in U.S. Pat. App. Pub. No. 2011/0087530,entitled “Systems and Methods to Provide Loyalty Programs,” thedisclosure of which is incorporated herein by reference.

FIG. 12 shows a system to provide offers according to one embodiment. InFIG. 12, users (101) can use the transaction terminals (105) to conductpayment transactions (e.g., using credit cards, debit cards, prepaidcards). The transaction terminals (105) may be operated by variousmerchants related to travel, including airline (441), hotel (443),broker (445), and others, such as rental car agencies, travel agents,etc.

In one embodiment, the transaction handler (103) processes thetransactions between the users (101) and merchants to generate thetransaction data (109), which can be used by the analytic tools, such asthe pattern detector (453) and the profile generator (121).

In FIG. 12, the users (101) may register via a gateway (447) for atravel program that may provide the users with VIP treatment at variousmerchants related to travel. The gateway (447) generates theregistration data (449), which can also be used by the analytic tools.

In one embodiment, the registration in the travel program allows thetransaction handler (103) to collect details about the travel relatedtransactions from the travel related merchants, such as options and/orpreferences in flights, rooms, cars, etc. selected in the travel relatedpurchases.

In one embodiment, the profile generator (121) can use the transactiondata (109), the account data (111), and/or the registration data (449)to generate (e.g., periodically) the user specific profile (131) tocharacterize the spending patterns of a traveler (e.g. users (101)). Theoffer selector (433) can use the user specific profile (131) in thedecision of providing the user specific offer (419), such as an upgrade,a discount, a reward, or a specific offer tailored to the needs of thetraveler. The needs may be identified from the user specific profile(131), or the transaction patterns identified by the pattern detector(453).

In one embodiment, the user specific profile (131) includes a score thatis indicative of a value of the traveler to the merchant, such as anairline (441), a hotel (443), a broker (445), etc. The value is computedbased at least in part on the transaction data (109).

In some embodiments, the value may also be determined based on eventdata (451). For example, when the traveler is predicted to travel due toa recent event, the value may be increased in light of the event. Forexample, if the traveler is likely to use the service of the merchant inresponse to the recent event (as determined or predicted based on thetransaction history of the traveler and/or the pattern of customers whohave similar behavior as the traveler), the value of the traveler ishigh for the merchant.

In one embodiment, the pattern detector (453) is configured to identifythe travel spending patterns from the transaction data (109), accountdata (111) and/or the event data (451). For example, the cause andeffect relationships between events and transactions can be identifiedvia statistically correlating the events and the various clusters oftransactions related to travel. The correlation can be used to predictfuture transactions, in response to similar events.

In one embodiment, the results generated by the pattern detector (453)are used in reports or to drive alerts (455). For example, the merchantsmay use a web portal (e.g., 143) of the transaction handler (103) toview reports on predictions of transaction patterns (e.g., in responseto a recent event) and to view segments of customers that may beinvolved in such transactions. For example, a merchant may select asegment of customers and request the transaction handler (103) toprovide advertisements/offers to the customers. For example, a merchantmay request the transaction handler (103) to target a segment ofcustomers, such that the merchant is alerted when one of the customersis visiting the merchant (e.g., making a transaction with the merchant,such as reserving a room, checking into a hotel, booking a flight,etc.). The merchant may be alerted via mobile phones, or via transactionterminals (105) (e.g., from which a transaction request is beingsubmitted for the traveler).

In some embodiments, the activities of the users (101) at points ofinteraction (e.g., web browser, mobile phone, billboard) can be tracked;and the advertisement or offers (419) can be presented to the user (101)on the points of interaction.

Further details about the transaction handler (103), profile generator(121), transaction terminal (105), and examples of delivery of targetedoffers to users can be found in the sections entitled “TRANSACTION DATABASED PORTAL,” “TRANSACTION TERMINAL,” “TRANSACTION PROFILE,”“AGGREGATED SPENDING PROFILE,” “ON ATM & POS TERMINAL,” “ON THIRD PARTYSITE,” and in other sections.

FIGS. 13-14 show methods to provide offers according to someembodiments.

In FIG. 13, a traveler having an account identifier (e.g., accountinformation (142) presented by the account identification device (141))is registered (501) in a travel program supported by the transactionhandler (103), which generates (503) transaction data (109) fromprocessing payments made via the account identifier of the traveler(e.g., user (101)). The transaction handler (103) is configured tocompute (505) a value score based on the transaction data (109) inresponse to receiving the account identifier (e.g., account number(302)) at a merchant related to travel, and provide (507) the valuescore of the traveler to the merchant for the determination of an offer(e.g., 419) to the traveler.

For example, the value score may be based on the spending pattern of thetraveler, such as the segments of travel related products or servicespurchased by the traveler, the amount and frequency of the correspondingtravel spending, etc. Based on the value score, the merchant related totravel (e.g., airline, hotel, rental car agency) may decide to offer thetraveler an upgrade, a special treatment, a reward, a discount, anincentive, etc., while the traveler is engaging with the merchant (e.g.,making a reservation, checking in, making a purchase). In oneembodiment, the value score is a selected one from the factor values(344) that relates most to the area of travel spending.

In some embodiments, the registration with the travel program mayrequire a fee; and the membership in the travel program entitles thetraveler to a set of predetermined benefits or offers, such as VIPtreatment, upgrades, reward points, etc.

In some embodiments, when the value score is above a threshold, thetraveler is entitled to a set of predetermined benefits or offers fromone or more groups of merchants related to travel; and when the valuescore is below a threshold, the benefits or offers may be reduced oreliminated.

In some embodiments, the transaction handler (103) determines a rewardscore (e.g., points) based on prior transactions; and the reward scorecan be used in a loyalty program (e.g., in accordance with the loyaltyprogram rules (185)) to determine offers (e.g., 419) to the traveler(e.g., 101).

In FIG. 14, a computing device is configured to identify (511)transactions related to travel spending, identify (513) events relatedto travel, correlate (515) the transactions related to travel spendingwith the events related to travel to generate correlation data, predict(517) spending patterns in response to an event related to travel usingthe correlation data, and provide (519) the predicted spending patternsto merchants.

For example, based on the correlation data, the computing device maypredict travel activities in a segment of travelers, which may or maynot be registered in a travel program. The computing device may providethe prediction to a group of merchants to allow the merchants to provideoffers to the cardholders to compete for their business.

In one embodiment, registration in a travel program allows thetransaction handler (103) to collect details about the travel relatedpurchases; and the details can be used in generating the correlationdata. The correlation data can then be used to predict the detailedtravel needs of cardholders who may not be registered in the travelprogram. For example, when the cardholders have similar transactionpatterns as identified without using information about the detailedneeds, the cardholders may be determined to have similar detailed needs.Thus, the correlation data to predict the detailed needs can be appliedto the cardholders who may not be members of the travel program.

FIG. 15 illustrates an example to provide offers according to oneembodiment. In one embodiment, VISA is as an example of an operator ofthe transaction handler (103). A cardholder/business traveler can use agateway (447) to opt in a program, via a consumer management unit thatgenerates traveler data (409), including enrollment data (411), such asa consent associated with the account information (142) associated withthe account identification device (141) of the traveler, mobile phoneinformation (413), such as records of mobile phone properties for thecustomization and provision of offers via mobile phones, and alertdelivery options selected by the traveler/consumer. In one embodiment,the traveler data (409) is stored in the data warehouse (149), or in aseparate data storage facility.

In one embodiment, the registration involves identifying the accountidentification device (141), such as a registered card of the cardholderor account holder, issued by an issuer operating the issuer processor(145). The account holder can use the account identification device(141) to transact (461) with the merchant (429), which sends thetransaction request to the acquirer processor (147). The transactionhandler (103) settles the transaction between the acquirer who operatesthe acquirer processor (147) to represent the merchant (429) and theissuer who operates the issuer processor (145) to represent thecardholder or account holder.

In one embodiment, the registered account identification device (141)can be used as a loyalty card for the travel program. Further detailsabout using a registered transaction card as a loyalty card can be foundin the section entitled “LOYALTY PROGRAM.”

In FIG. 15, the gateway (447) provides the enrollment data (411) to thetransaction handler (103); and the transaction handler (103) providesrelevant transaction data (109) and/or transaction alerts to the gateway(447). The gateway (447) may further provide the relevant transactiondata (109) and/or transaction alert to the hotel broker (405), which mayprovide offers (e.g., 419) to the cardholder via the gateway (447).

In one embodiment, the transaction handler (103) includes a scoregenerator (431), a pattern detector (453), and a model generator (435)configured to use a statistical model to score patterns, and to identifycause and effect relationships between events (e.g., identified by theevent data (451)) that impact travel and transactions related to travelspending. In one embodiment, the score generator (431) generates thescore (421) based at least in part on the transaction data (109) and/orthe event data (451). In one embodiment, the pattern detector (453) usesthe transaction data (109), the event data (451), the consumer data(425) and the merchant data (427) to generate the correlation data(423), such as the patterns and the cause and effect relationshipsgenerated according to cardholder segments and/or merchant code.

In one embodiment, the transaction handler (103) maintains a databasefor customer/merchant scores (421) and event triggers, and may furtheruse third party data (407) to predict travel spending.

In one embodiment, the model generator (435) is configured to generatestatistical models for the determination of the score (421) and/or thecorrelation data (423), using the transaction data (109) of theregistered travelers. For example, in one embodiment, the modelgenerator (435) is configured to use the data of the opt-in customers toprime model predictions over time to grow intelligence based againstother cardholders (e.g., non opt-in cardholders).

In one embodiment, the hoteliers (401) can access the data servicesplatform (403) for aggregated business intelligence reports, generatedby the transaction handler (103), which has the ability to serve upideal customer segments by merchant category code and forecastpredictions on what is most likely to happen based on knownenvironmental, airline, hotel and car data.

In FIG. 15, the transaction handler (103) has a data services platform(403) that is configured to communicate with third party systems (e.g.,407), merchants (e.g., 429 and 401), and/or cardholders (e.g., 101). Inone embodiment, the data services platform (403) includes subscriptionservices, report delivery options, a web portal (e.g., 143) for businessintelligence, a data store for real time data service objects, webservices, services clients, and application programming interfaces (API)for ab initio queries (e.g., expressed in a structured query language(SQL)), business intelligence, etc.

In one embodiment, the hotel broker (405) is provided with real timevalue scores of customers, via real time interface between thetransaction handler (103) and third party systems.

In one embodiment, when the user (101) (e.g., a business cardholder)checks in (463) to participating hotels, the value score (421) of thecardholder is served up for VIP treatment/upgrades. In one embodiment,the user (101) has previously opted in the program to receive the offer.In one embodiment, the user (101) is a traveler that has not yet optedin the program; and the transaction data (109) of the travelers who haveopted in are used to generate and/or tune the model for the value scores(421); and the model is applied to the user (101) who has not yet optedin to predict the value score (421) for the user (101).

In one embodiment, the transaction handler (103) is configured toprocess transactions of a traveler (e.g., user (101)). Each of thetransactions is processed to make a payment from an issuer processor(145) to an acquirer processor (147) via the transaction handler (103)in response to an account identifier of the traveler, as issued by theissuer, being submitted by a merchant (429) to the acquirer. The issuermakes the payment on behalf of the traveler; and the acquirer receivesthe payment on behalf of the merchant (429).

In one embodiment, the score generator (431) is coupled with the datawarehouse (149) of the transaction handler (103) to compute a score(421) of the traveler based on the transactions processed by thetransaction handler (103). The score (421) is designed to be indicativeof a value of the traveler to merchants of a predetermined type, such ashoteliers, transportation providers, etc.

In one embodiment, the data services platform (403) is configured toprovide the value score (421) of the traveler to a first merchant (e.g.,hotelier (401)) of the predetermined type in response to the travelerbeing identified to the transaction handler (103) via the accountidentifier, such as when the user (101) uses the account identificationdevice (141) to transact with the hotelier (401) to make a reservation,to check into a hotel, etc.

In one embodiment, the value score (421) of the traveler facilitates adecision by the first merchant to provide an offer to the traveler, suchas a VIP treatment, a service upgrade at a discount price or without afee, a free night stay, etc.

In one embodiment, the gateway (447) is configured to register thetraveler based on the account identifier provided by the accountidentification device (141) and/or enroll the traveler in a program thatprovides travel related incentives to the enrolled travelers who areenrolled in the program.

In one embodiment, the model generator (435) is configured to generate amodel to compute the value score (421) of the traveler based ontransaction data (109) of the travelers who are enrolled in the program.In one embodiment, the model is applied by the score generator (431) tothe traveler who has not yet been enrolled in the program to compute thevalue score (421) of the traveler.

In one embodiment, the value score (421) is determined based on a factorvalue (e.g., 344) of an aggregated spending profile (341) of thetraveler; and the factor value (e.g., 344) is relevant to thepredetermined type of merchants. In one embodiment, the factor value(e.g., 344) is computed using the transaction data (109) of the travelerbased on factor definitions (331) determined from a factor analysis(327) of transaction data (109) of a plurality of users (e.g., 101),which may or may not include the traveler. In one embodiment, the valuescore (421) is determined based on a distance to a spending clusteridentified from a cluster analysis (329) of transaction data (109) of aplurality of users. Details and examples of an aggregated spendingprofile (341) are provided in the section entitled “AGGREGATED SPENDINGPROFILE.”

In one embodiment, the value score (421) is further based on dataidentifying one or more events related to travel, such as a spendingpattern that is predicted to occur using the model generated by themodel generator (435) as a response to one or more travel related events(e.g., announced in a news medium, discussed in a social networkingwebsite, etc.)

In one embodiment, the model generator (435) is configured to identifytransaction data (109) related to travel spending, identify datarepresenting events (451), and correlate the transaction data (109)related to the travel spending and the data representing the events(451) to generate a predictive model. The pattern detector (453) isconfigured to use the predictive model to predict spending patterns inresponse to an event.

In one embodiment, the pattern detector (453) is configured to use thepredictive model to identify a set of customers based on the spendingpatterns. After a plurality of merchants are registered in a program toreceive reports or alerts, the data services platform (403) providesinformation to identify the set of customers to the merchants who haveregistered in the program.

In one embodiment, the offer selector (433) is configured to use thepredicted spending patterns, the information identifying the set ofcustomers, and/or the value score (421) to identify an offer (419)relevant to the spending patterns. The portal (143) of the transactionhandler (103), the data services platform (403), or the gateway (447)may provide the offer (419) to the set of customers on behalf of amerchant, such as the hotelier (401).

In one embodiment, the pattern detector (453) is coupled with the datawarehouse (149) to identify correlation data (423) that relatestransaction patterns in the transaction data (109) and the eventsidentified in the event data (451); and in response to an occurrence ofa first event, the portal (143) of the transaction handler (103) isconfigured to provide a report (455) of a predicted spending patternidentified based on the correlation data (423) and data identifying thefirst event.

In one embodiment, the data services platform (403) is configured toprovide the value score (421) of the traveler via at least one of: aquery application programming interface, a web service, and asubscription service.

In one embodiment, the value score (421) is determined based at least inpart on the predicted spending pattern.

In one embodiment, the gateway (447) is configured to register accountidentifiers and mobile phone information of travelers and to provide tothe travelers, via communications to mobile phones of the travelers,travel related offers (e.g., 419) identified based on the predictedspending pattern.

In one embodiment, a computing apparatus or system includes thetransaction handler (103), the data warehouse (149), the gateway (447),the data services platform (403), the score generator (431), the patterndetector (453), the model generator (435), the offer selector (433),and/or the profile generator (121). Some details about the system in oneembodiment are provided in the sections entitled “SYSTEM,” “CENTRALIZEDDATA WAREHOUSE” and “HARDWARE.”

Variations

Some embodiments use more or fewer components than those illustrated inFIGS. 1 and 4-7. For example, in one embodiment, the user specificprofile (131) is used by a search engine to prioritize search results.In one embodiment, the correlator (117) is to correlate transactionswith online activities, such as searching, web browsing, and socialnetworking, instead of or in addition to the user specific advertisementdata (119). In one embodiment, the correlator (117) is to correlatetransactions and/or spending patterns with news announcements, marketchanges, events, natural disasters, etc. In one embodiment, the data tobe correlated by the correlator with the transaction data (109) may notbe personalized via the user specific profile (131) and may not be userspecific. In one embodiment, multiple different devices are used at thepoint of interaction (107) for interaction with the user (101); and someof the devices may not be capable of receiving input from the user(101). In one embodiment, there are transaction terminals (105) toinitiate transactions for a plurality of users (101) with a plurality ofdifferent merchants. In one embodiment, the account information (142) isprovided to the transaction terminal (105) directly (e.g., via phone orInternet) without the use of the account identification device (141).

In one embodiment, at least some of the profile generator (121),correlator (117), profile selector (129), and advertisement selector(133) are controlled by the entity that operates the transaction handler(103). In another embodiment, at least some of the profile generator(121), correlator (117), profile selector (129), and advertisementselector (133) are not controlled by the entity that operates thetransaction handler (103).

For example, in one embodiment, the entity operating the transactionhandler (103) provides the intelligence (e.g., transaction profiles(127) or the user specific profile (131)) for the selection of theadvertisement; and a third party (e.g., a web search engine, apublisher, or a retailer) may present the advertisement in a contextoutside a transaction involving the transaction handler (103) before theadvertisement results in a purchase.

For example, in one embodiment, the customer may interact with the thirdparty at the point of interaction (107); and the entity controlling thetransaction handler (103) may allow the third party to query forintelligence information (e.g., transaction profiles (127), or the userspecific profile (131)) about the customer using the user data (125),thus informing the third party of the intelligence information fortargeting the advertisements, which can be more useful, effective andcompelling to the user (101). For example, the entity operating thetransaction handler (103) may provide the intelligence informationwithout generating, identifying or selecting advertisements; and thethird party receiving the intelligence information may identify, selectand/or present advertisements.

Through the use of the transaction data (109), account data (111),correlation results (123), the context at the point of interaction,and/or other data, relevant and compelling messages or advertisementscan be selected for the customer at the points of interaction (e.g.,107) for targeted advertising. The messages or advertisements are thusdelivered at the optimal time for influencing or reinforcing brandperceptions and revenue-generating behavior. The customers receive theadvertisements in the media channels that they like and/or use mostfrequently.

In one embodiment, the transaction data (109) includes transactionamounts, the identities of the payees (e.g., merchants), and the dateand time of the transactions. The identities of the payees can becorrelated to the businesses, services, products and/or locations of thepayees. For example, the transaction handler (103) maintains a databaseof merchant data, including the merchant locations, businesses,services, products, etc. Thus, the transaction data (109) can be used todetermine the purchase behavior, pattern, preference, tendency,frequency, trend, budget and/or propensity of the customers in relationto various types of businesses, services and/or products and in relationto time.

In one embodiment, the products and/or services purchased by the user(101) are also identified by the information transmitted from themerchants or service providers. Thus, the transaction data (109) mayinclude identification of the individual products and/or services, whichallows the profile generator (121) to generate transaction profiles(127) with fine granularity or resolution. In one embodiment, thegranularity or resolution may be at a level of distinct products andservices that can be purchased (e.g., stock-keeping unit (SKU) level),or category or type of products or services, or vendor of products orservices, etc.

The profile generator (121) may consolidate transaction data for aperson having multiple accounts to derive intelligence information aboutthe person to generate a profile for the person (e.g., transactionprofiles (127), or the user specific profile (131)).

The profile generator (121) may consolidate transaction data for afamily having multiple accounts held by family members to deriveintelligence information about the family to generate a profile for thefamily (e.g., transaction profiles (127), or the user specific profile(131)).

Similarly, the profile generator (121) may consolidate transaction datafor a group of persons, after the group is identified by certaincharacteristics, such as gender, income level, geographical location orregion, preference, characteristics of past purchases (e.g., merchantcategories, purchase types), cluster, propensity, demographics, socialnetworking characteristics (e.g., relationships, preferences, activitieson social networking websites), etc. The consolidated transaction datacan be used to derive intelligence information about the group togenerate a profile for the group (e.g., transaction profiles (127), orthe user specific profile (131)).

In one embodiment, the profile generator (121) may consolidatetransaction data according to the user data (125) to generate a profilespecific to the user data (125).

Since the transaction data (109) are records and history of pastpurchases, the profile generator (121) can derive intelligenceinformation about a customer using an account, a customer using multipleaccounts, a family, a company, or other groups of customers, about whatthe targeted audience is likely to purchase in the future, howfrequently, and their likely budgets for such future purchases.Intelligence information is useful in selecting the advertisements thatare most useful, effective and compelling to the customer, thusincreasing the efficiency and effectiveness of the advertising process.

In one embodiment, the transaction data (109) are enhanced withcorrelation results (123) correlating past advertisements and purchasesthat result at least in part from the advertisements. Thus, theintelligence information can be more accurate in assisting with theselection of the advertisements. The intelligence information may notonly indicate what the audience is likely to purchase, but also howlikely the audience is to be influenced by advertisements for certainpurchases, and the relative effectiveness of different forms ofadvertisements for the audience. Thus, the advertisement selector (133)can select the advertisements to best use the opportunity to communicatewith the audience. Further, the transaction data (109) can be enhancedvia other data elements, such as program enrollment, affinity programs,redemption of reward points (or other types of offers), onlineactivities, such as web searches and web browsing, social networkinginformation, etc., based on the account data (111) and/or other data,such as non-transactional data discussed in U.S. patent application Ser.No. 12/614,603, filed Nov. 9, 2009 and entitled “Analyzing LocalNon-Transactional Data with Transactional Data in Predictive Models,”the disclosure of which is hereby incorporated herein by reference.

In one embodiment, the entity operating the transaction handler (103)provides the intelligence information in real-time as the request forthe intelligence information occurs. In other embodiments, the entityoperating the transaction handler (103) may provide the intelligenceinformation in batch mode. The intelligence information can be deliveredvia online communications (e.g., via an application programminginterface (API) on a website, or other information server), or viaphysical transportation of a computer readable media that stores thedata representing the intelligence information.

In one embodiment, the intelligence information is communicated tovarious entities in the system in a way similar to, and/or in parallelwith the information flow in the transaction system to move money. Thetransaction handler (103) routes the information in the same way itroutes the currency involved in the transactions.

In one embodiment, the portal (143) provides a user interface to allowthe user (101) to select items offered on different merchant websitesand store the selected items in a wish list for comparison, reviewing,purchasing, tracking, etc. The information collected via the wish listcan be used to improve the transaction profiles (127) and deriveintelligence on the needs of the user (101); and targeted advertisementscan be delivered to the user (101) via the wish list user interfaceprovided by the portal (143). Examples of user interface systems tomanage wish lists are provided in U.S. Pat. App. Pub. No. 2010/0174623,entitled “System and Method for Managing Items of Interest Selected fromOnline Merchants,” the disclosure of which is hereby incorporated hereinby reference.

Aggregated Spending Profile

In one embodiment, the characteristics of transaction patterns ofcustomers are profiled via clusters, factors, and/or categories ofpurchases. The transaction data (109) may include transaction records(301); and in one embodiment, an aggregated spending profile (341) isgenerated from the transaction records (301), in a way illustrated inFIG. 2, to summarize the spending behavior reflected in the transactionrecords (301).

In one embodiment, each of the transaction records (301) is for aparticular transaction processed by the transaction handler (103). Eachof the transaction records (301) provides information about theparticular transaction, such as the account number (302) of the consumeraccount (146) used to pay for the purchase, the date (303) (and/or time)of the transaction, the amount (304) of the transaction, the ID (305) ofthe merchant who receives the payment, the category (306) of themerchant, the channel (307) through which the purchase was made, etc.Examples of channels include online, offline in-store, via phone, etc.In one embodiment, the transaction records (301) may further include afield to identify a type of transaction, such as card-present,card-not-present, etc.

In one embodiment, a “card-present” transaction involves physicallypresenting the account identification device (141), such as a financialtransaction card, to the merchant (e.g., via swiping a credit card at aPOS terminal of a merchant); and a “card-not-present” transactioninvolves presenting the account information (142) of the consumeraccount (146) to the merchant to identify the consumer account (146)without physically presenting the account identification device (141) tothe merchant or the transaction terminal (105).

In one embodiment, certain information about the transaction can belooked up in a separate database based on other information recorded forthe transaction. For example, a database may be used to storeinformation about merchants, such as the geographical locations of themerchants, categories of the merchants, etc. Thus, the correspondingmerchant information related to a transaction can be determined usingthe merchant ID (305) recorded for the transaction.

In one embodiment, the transaction records (301) may further includedetails about the products and/or services involved in the purchase. Forexample, a list of items purchased in the transaction may be recordedtogether with the respective purchase prices of the items and/or therespective quantities of the purchased items. The products and/orservices can be identified via stock-keeping unit (SKU) numbers, orproduct category IDs. The purchase details may be stored in a separatedatabase and be looked up based on an identifier of the transaction.

When there is voluminous data representing the transaction records(301), the spending patterns reflected in the transaction records (301)can be difficult to recognize by an ordinary person.

In one embodiment, the voluminous transaction records (301) aresummarized (335) into aggregated spending profiles (e.g., 341) toconcisely present the statistical spending characteristics reflected inthe transaction records (301). The aggregated spending profile (341)uses values derived from statistical analysis to present the statisticalcharacteristics of transaction records (301) of an entity in a way easyto understand by an ordinary person.

In FIG. 2, the transaction records (301) are summarized (335) via factoranalysis (327) to condense the variables (e.g., 313, 315) and viacluster analysis (329) to segregate entities by spending patterns.

In FIG. 2, a set of variables (e.g., 311, 313, 315) are defined based onthe parameters recorded in the transaction records (301). The variables(e.g., 311, 313, and 315) are defined in a way to have meanings easilyunderstood by an ordinary person. For example, variables (311) measurethe aggregated spending in super categories; variables (313) measure thespending frequencies in various areas; and variables (315) measure thespending amounts in various areas. In one embodiment, each of the areasis identified by a merchant category (306) (e.g., as represented by amerchant category code (MCC), a North American Industry ClassificationSystem (NAICS) code, or a similarly standardized category code). Inother embodiments, an area may be identified by a product category, aSKU number, etc.

In one embodiment, a variable of a same category (e.g., frequency (313)or amount (315)) is defined to be aggregated over a set of mutuallyexclusive areas. A transaction is classified in only one of the mutuallyexclusive areas. For example, in one embodiment, the spending frequencyvariables (313) are defined for a set of mutually exclusive merchants ormerchant categories. Transactions falling with the same category areaggregated.

Examples of the spending frequency variables (313) and spending amountvariables (315) defined for various merchant categories (e.g., 306) inone embodiment are provided in U.S. Pat. App. Pub. No. 2010/0306029,entitled “Cardholder Clusters,” and in Prov. U.S. Pat. App. Ser. No.61/182,806, filed Jun. 1, 2009 and entitled “Cardholder Clusters,” thedisclosures of which applications are hereby incorporated herein byreference.

In one embodiment, super categories (311) are defined to group thecategories (e.g., 306) used in transaction records (301). The supercategories (311) can be mutually exclusive. For example, each merchantcategory (306) is classified under only one super merchant category butnot any other super merchant categories. Since the generation of thelist of super categories typically requires deep domain knowledge aboutthe businesses of the merchants in various categories, super categories(311) are not used in one embodiment.

In one embodiment, the aggregation (317) includes the application of thedefinitions (309) for these variables (e.g., 311, 313, and 315) to thetransaction records (301) to generate the variable values (321). Thetransaction records (301) are aggregated to generate aggregatedmeasurements (e.g., variable values (321)) that are not specific to aparticular transaction, such as frequencies of purchases made withdifferent merchants or different groups of merchants, the amounts spentwith different merchants or different groups of merchants, and thenumber of unique purchases across different merchants or differentgroups of merchants, etc. The aggregation (317) can be performed for aparticular time period and for entities at various levels.

In one embodiment, the transaction records (301) are aggregatedaccording to a buying entity. The aggregation (317) can be performed ataccount level, person level, family level, company level, neighborhoodlevel, city level, region level, etc. to analyze the spending patternsacross various areas (e.g., sellers, products or services) for therespective aggregated buying entity. For example, the transactionrecords (301) for a particular account (e.g., presented by the accountnumber (302)) can be aggregated for an account level analysis. Toaggregate the transaction records (301) in account level, thetransactions with a specific merchant or merchants in a specificcategory are counted according to the variable definitions (309) for aparticular account to generate a frequency measure (e.g., 313) for theaccount relative to the specific merchant or merchant category; and thetransaction amounts (e.g., 304) with the specific merchant or thespecific category of merchants are summed for the particular account togenerate an average spending amount for the account relative to thespecific merchant or merchant category. For example, the transactionrecords (301) for a particular person having multiple accounts can beaggregated for a person level analysis, the transaction records (301)aggregated for a particular family for a family level analysis, and thetransaction records (301) for a particular business aggregated for abusiness level analysis.

The aggregation (317) can be performed for a predetermined time period,such as for the transactions occurring in the past month, in the pastthree months, in the past twelve months, etc.

In another embodiment, the transaction records (301) are aggregatedaccording to a selling entity. The spending patterns at the sellingentity across various buyers, products or services can be analyzed. Forexample, the transaction records (301) for a particular merchant havingtransactions with multiple accounts can be aggregated for a merchantlevel analysis. For example, the transaction records (301) for aparticular merchant group can be aggregated for a merchant group levelanalysis.

In one embodiment, the aggregation (317) is formed separately fordifferent types of transactions, such as transactions made online,offline, via phone, and/or “card-present” transactions vs.“card-not-present” transactions, which can be used to identify thespending pattern differences among different types of transactions.

In one embodiment, the variable values (e.g., 323, 324, . . . , 325)associated with an entity ID (322) are considered the random samples ofthe respective variables (e.g., 311, 313, 315), sampled for the instanceof an entity represented by the entity ID (322). Statistical analyses(e.g., factor analysis (327) and cluster analysis (329)) are performedto identify the patterns and correlations in the random samples.

For example, a cluster analysis (329) can identify a set of clusters andthus cluster definitions (333) (e.g., the locations of the centroids ofthe clusters). In one embodiment, each entity ID (322) is represented asa point in a mathematical space defined by the set of variables; and thevariable values (323, 324, . . . , 325) of the entity ID (322) determinethe coordinates of the point in the space and thus the location of thepoint in the space. Various points may be concentrated in variousregions; and the cluster analysis (329) is configured to formulate thepositioning of the points to drive the clustering of the points. Inother embodiments, the cluster analysis (329) can also be performedusing the techniques of Self Organizing Maps (SOM), which can identifyand show clusters of multi-dimensional data using a representation on atwo-dimensional map.

Once the cluster definitions (333) are obtained from the clusteranalysis (329), the identity of the cluster (e.g., cluster ID (343))that contains the entity ID (322) can be used to characterize spendingbehavior of the entity represented by the entity ID (322). The entitiesin the same cluster are considered to have similar spending behaviors.

Similarities and differences among the entities, such as accounts,individuals, families, etc., as represented by the entity ID (e.g., 322)and characterized by the variable values (e.g., 323, 324, . . . , 325)can be identified via the cluster analysis (329). In one embodiment,after a number of clusters of entity IDs are identified based on thepatterns of the aggregated measurements, a set of profiles can begenerated for the clusters to represent the characteristics of theclusters. Once the clusters are identified, each of the entity IDs(e.g., corresponding to an account, individual, family) can be assignedto one cluster; and the profile for the corresponding cluster may beused to represent, at least in part, the entity (e.g., account,individual, family). Alternatively, the relationship between an entity(e.g., an account, individual, family) and one or more clusters can bedetermined (e.g., based on a measurement of closeness to each cluster).Thus, the cluster related data can be used in a transaction profile (127or 341) to provide information about the behavior of the entity (e.g.,an account, an individual, a family).

In one embodiment, more than one set of cluster definitions (333) isgenerated from cluster analyses (329). For example, cluster analyses(329) may generate different sets of cluster solutions corresponding todifferent numbers of identified clusters. A set of cluster IDs (e.g.,343) can be used to summarize (335) the spending behavior of the entityrepresented by the entity ID (322), based on the typical spendingbehavior of the respective clusters. In one example, two clustersolutions are obtained; one of the cluster solutions has 17 clusters,which classify the entities in a relatively coarse manner; and the othercluster solution has 55 clusters, which classify the entities in arelative fine manner. A cardholder can be identified by the spendingbehavior of one of the 17 clusters and one of the 55 clusters in whichthe cardholder is located. Thus, the set of cluster IDs corresponding tothe set of cluster solutions provides a hierarchical identification ofan entity among clusters of different levels of resolution. The spendingbehavior of the clusters is represented by the cluster definitions(333), such as the parameters (e.g., variable values) that define thecentroids of the clusters.

In one embodiment, the random variables (e.g., 313 and 315) as definedby the definitions (309) have certain degrees of correlation and are notindependent from each other. For example, merchants of differentmerchant categories (e.g., 306) may have overlapping business, or havecertain business relationships. For example, certain products and/orservices of certain merchants have cause and effect relationships. Forexample, certain products and/or services of certain merchants aremutually exclusive to a certain degree (e.g., a purchase from onemerchant may have a level of probability to exclude the user (101) frommaking a purchase from another merchant). Such relationships may becomplex and difficult to quantify by merely inspecting the categories.Further, such relationships may shift over time as the economy changes.

In one embodiment, a factor analysis (327) is performed to reduce theredundancy and/or correlation among the variables (e.g., 313, 315). Thefactor analysis (327) identifies the definitions (331) for factors, eachof which represents a combination of the variables (e.g., 313, 315).

In one embodiment, a factor is a linear combination of a plurality ofthe aggregated measurements (e.g., variables (313, 315)) determined forvarious areas (e.g., merchants or merchant categories, products orproduct categories). Once the relationship between the factors and theaggregated measurements is determined via factor analysis, the valuesfor the factors can be determined from the linear combinations of theaggregated measurements and be used in a transaction profile (127 or341) to provide information on the behavior of the entity represented bythe entity ID (e.g., an account, an individual, a family).

Once the factor definitions (331) are obtained from the factor analysis(327), the factor definitions (331) can be applied to the variablevalues (321) to determine factor values (344) for the aggregatedspending profile (341). Since redundancy and correlation are reduced inthe factors, the number of factors is typically much smaller than thenumber of the original variables (e.g., 313, 315). Thus, the factorvalues (344) represent the concise summary of the original variables(e.g., 313, 315).

For example, there may be thousands of variables on spending frequencyand amount for different merchant categories; and the factor analysis(327) can reduce the factor number to less than one hundred (and evenless than twenty). In one example, a twelve-factor solution is obtained,which allows the use of twelve factors to combine the thousands of theoriginal variables (313, 315); and thus, the spending behavior inthousands of merchant categories can be summarized via twelve factorvalues (344). In one embodiment, each factor is combination of at leastfour variables; and a typical variable has contributions to more thanone factor.

In one example, hundreds or thousands of transaction records (301) of acardholder are converted into hundreds or thousands of variable values(321) for various merchant categories, which are summarized (335) viathe factor definitions (331) and cluster definitions (333) into twelvefactor values (344) and one or two cluster IDs (e.g., 343). Thesummarized data can be readily interpreted by a human to ascertain thespending behavior of the cardholder. A user (101) may easily specify aspending behavior requirement formulated based on the factor values(344) and the cluster IDs (e.g., to query for a segment of customers, orto request the targeting of a segment of customers). The reduced size ofthe summarized data reduces the need for data communication bandwidthfor communicating the spending behavior of the cardholder over a networkconnection and allows simplified processing and utilization of the datarepresenting the spending behavior of the cardholder.

In one embodiment, the behavior and characteristics of the clusters arestudied to identify a description of a type of representative entitiesthat are found in each of the clusters. The clusters can be named basedon the type of representative entities to allow an ordinary person toeasily understand the typical behavior of the clusters.

In one embodiment, the behavior and characteristics of the factors arealso studied to identify dominant aspects of each factor. The clusterscan be named based on the dominant aspects to allow an ordinary personto easily understand the meaning of a factor value.

In FIG. 2, an aggregated spending profile (341) for an entityrepresented by an entity ID (e.g., 322) includes the cluster ID (343)and factor values (344) determined based on the cluster definitions(333) and the factor definitions (331). The aggregated spending profile(341) may further include other statistical parameters, such asdiversity index (342), channel distribution (345), category distribution(346), zip code (347), etc., as further discussed below.

In one embodiment, the diversity index (342) may include an entropyvalue and/or a Gini coefficient, to represent the diversity of thespending by the entity represented by the entity ID (322) acrossdifferent areas (e.g., different merchant categories (e.g., 306)). Whenthe diversity index (342) indicates that the diversity of the spendingdata is under a predetermined threshold level, the variable values(e.g., 323, 324, . . . , 325) for the corresponding entity ID (322) maybe excluded from the cluster analysis (329) and/or the factor analysis(327) due to the lack of diversity. When the diversity index (342) ofthe aggregated spending profile (341) is lower than a predeterminedthreshold, the factor values (344) and the cluster ID (343) may notaccurately represent the spending behavior of the corresponding entity.

In one embodiment, the channel distribution (345) includes a set ofpercentage values that indicate the percentages of amounts spent indifferent purchase channels, such as online, via phone, in a retailstore, etc.

In one embodiment, the category distribution (346) includes a set ofpercentage values that indicate the percentages of spending amounts indifferent super categories (311). In one embodiment, thousands ofdifferent merchant categories (e.g., 306) are represented by MerchantCategory Codes (MCC), or North American Industry Classification System(NAICS) codes in transaction records (301). These merchant categories(e.g., 306) are classified or combined into less than one hundred supercategories (or less than twenty). In one example, fourteen supercategories are defined based on domain knowledge.

In one embodiment, the aggregated spending profile (341) includes theaggregated measurements (e.g., frequency, average spending amount)determined for a set of predefined, mutually exclusive merchantcategories (e.g., super categories (311)). Each of the super merchantcategories represents a type of products or services a customer maypurchase. A transaction profile (127 or 341) may include the aggregatedmeasurements for each of the set of mutually exclusive merchantcategories. The aggregated measurements determined for the predefined,mutually exclusive merchant categories can be used in transactionprofiles (127 or 341) to provide information on the behavior of arespective entity (e.g., an account, an individual, or a family).

In one embodiment, the zip code (347) in the aggregated spending profile(341) represents the dominant geographic area in which the spendingassociated with the entity ID (322) occurred. Alternatively or incombination, the aggregated spending profile (341) may include adistribution of transaction amounts over a set of zip codes that accountfor a majority of the transactions or transaction amounts (e.g., 90%).

In one embodiment, the factor analysis (327) and cluster analysis (329)are used to summarize the spending behavior across various areas, suchas different merchants characterized by merchant category (306),different products and/or services, different consumers, etc. Theaggregated spending profile (341) may include more or fewer fields thanthose illustrated in FIG. 2. For example, in one embodiment, theaggregated spending profile (341) further includes an aggregatedspending amount for a period of time (e.g., the past twelve months); inanother embodiment, the aggregated spending profile (341) does notinclude the category distribution (346); and in a further embodiment,the aggregated spending profile (341) may include a set of distancemeasures to the centroids of the clusters. The distance measures may bedefined based on the variable values (323, 324, . . . , 325), or basedon the factor values (344). The factor values of the centroids of theclusters may be estimated based on the entity ID (e.g., 322) that isclosest to the centroid in the respective cluster.

Other variables can be used in place of, or in additional to, thevariables (311, 313, 315) illustrated in FIG. 2. For example, theaggregated spending profile (341) can be generated using variablesmeasuring shopping radius/distance from the primary address of theaccount holder to the merchant site for offline purchases. When suchvariables are used, the transaction patterns can be identified based atleast in part on clustering according to shopping radius/distance andgeographic regions. Similarly, the factor definition (331) may includethe consideration of the shopping radius/distance. For example, thetransaction records (301) may be aggregated based on the ranges ofshopping radius/distance and/or geographic regions. For example, thefactor analysis can be used to determine factors that naturally combinegeographical areas based on the correlations in the spending patterns invarious geographical areas.

In one embodiment, the aggregation (317) may involve the determinationof a deviation from a trend or pattern. For example, an account makes acertain number of purchases a week at a merchant over the past 6 months.However, in the past 2 weeks the number of purchases is less than theaverage number per week. A measurement of the deviation from the trendor pattern can be used (e.g., in a transaction profile (127 or 341) as aparameter, or in variable definitions (309) for the factor analysis(327) and/or the cluster analysis) to define the behavior of an account,an individual, a family, etc.

FIG. 3 shows a method to generate an aggregated spending profileaccording to one embodiment. In FIG. 3, computation models areestablished (351) for variables (e.g., 311, 313, and 315). In oneembodiment, the variables are defined in a way to capture certainaspects of the spending statistics, such as frequency, amount, etc.

In FIG. 3, data from related accounts are combined (353). For example,when an account number change has occurred for a cardholder in the timeperiod under analysis, the transaction records (301) under the differentaccount numbers of the same cardholder are combined under one accountnumber that represents the cardholder. For example, when the analysis isperformed at a person level (or family level, business level, socialgroup level, city level, or region level), the transaction records (301)in different accounts of the person (or family, business, social group,city or region) can be combined under one entity ID (322) thatrepresents the person (or family, business, social group, city orregion).

In one embodiment, recurrent/installment transactions are combined(355). For example, multiple monthly payments may be combined andconsidered as one single purchase.

In FIG. 3, account data are selected (357) according to a set ofcriteria related to activity, consistency, diversity, etc.

For example, when a cardholder uses a credit card solely to purchasegas, the diversity of the transactions by the cardholder is low. In sucha case, the transactions in the account of the cardholder may not bestatistically meaningful to represent the spending pattern of thecardholder in various merchant categories. Thus, in one embodiment, ifthe diversity of the transactions associated with an entity ID (322) isbelow a threshold, the variable values (e.g., 323, 324, . . . , 325)corresponding to the entity ID (322) are not used in the clusteranalysis (329) and/or the factor analysis (327). The diversity can beexamined based on the diversity index (342) (e.g., entropy or Ginicoefficient), or based on counting the different merchant categories inthe transactions associated with the entity ID (322); and when the countof different merchant categories is fewer than a threshold (e.g., 5),the transactions associated with the entity ID (322) are not used in thecluster analysis (329) and/or the factor analysis (327) due to the lackof diversity.

For example, when a cardholder uses a credit card only sporadically(e.g., when running out of cash), the limited transactions by thecardholder may not be statistically meaningful in representing thespending behavior of the cardholder. Thus, in one embodiment, when thenumbers of transactions associated with an entity ID (322) is below athreshold, the variable values (e.g., 323, 324, . . . , 325)corresponding to the entity ID (322) are not used in the clusteranalysis (329) and/or the factor analysis (327).

For example, when a cardholder has only used a credit card during aportion of the time period under analysis, the transaction records (301)during the time period may not reflect the consistent behavior of thecardholder for the entire time period. Consistency can be checked invarious ways. In one example, if the total number of transactions duringthe first and last months of the time period under analysis is zero, thetransactions associated with the entity ID (322) are inconsistent in thetime period and thus are not used in the cluster analysis (329) and/orthe factor analysis (327). Other criteria can be formulated to detectinconsistency in the transactions.

In FIG. 3, the computation models (e.g., as represented by the variabledefinitions (309)) are applied (359) to the remaining account data(e.g., transaction records (301)) to obtain data samples for thevariables. The data points associated with the entities, other thanthose whose transactions fail to meet the minimum requirements foractivity, consistency, diversity, etc., are used in factor analysis(327) and cluster analysis (329).

In FIG. 3, the data samples (e.g., variable values (321)) are used toperform (361) factor analysis (327) to identify factor solutions (e.g.,factor definitions (331)). The factor solutions can be adjusted (363) toimprove similarity in factor values of different sets of transactiondata (109). For example, factor definitions (331) can be applied to thetransactions in the time period under analysis (e.g., the past twelvemonths) and be applied separately to the transactions in a prior timeperiod (e.g., the twelve months before the past twelve months) to obtaintwo sets of factor values. The factor definitions (331) can be adjustedto improve the correlation between the two set of factor values.

The data samples can also be used to perform (365) cluster analysis(329) to identify cluster solutions (e.g., cluster definitions (333)).The cluster solutions can be adjusted (367) to improve similarity incluster identifications based on different sets of transaction data(109). For example, cluster definitions (333) can be applied to thetransactions in the time period under analysis (e.g., the past twelvemonths) and be applied separately to the transactions in a prior timeperiod (e.g., the twelve months before the past twelve months) to obtaintwo sets of cluster identifications for various entities. The clusterdefinitions (333) can be adjusted to improve the correlation between thetwo set of cluster identifications.

In one embodiment, the number of clusters is determined from clusteringanalysis. For example, a set of cluster seeds can be initiallyidentified and used to run a known clustering algorithm. The sizes ofdata points in the clusters are then examined. When a cluster containsless than a predetermined number of data points, the cluster may beeliminated to rerun the clustering analysis.

In one embodiment, standardizing entropy is added to the clustersolution to obtain improved results.

In one embodiment, human understandable characteristics of the factorsand clusters are identified (369) to name the factors and clusters. Forexample, when the spending behavior of a cluster appears to be thebehavior of an internet loyalist, the cluster can be named “internetloyalist” such that if a cardholder is found to be in the “internetloyalist” cluster, the spending preferences and patterns of thecardholder can be easily perceived.

In one embodiment, the factor analysis (327) and the cluster analysis(329) are performed periodically (e.g., once a year, or six months) toupdate the factor definitions (331) and the cluster definitions (333),which may change as the economy and the society change over time.

In FIG. 3, transaction data (109) are summarized (371) using the factorsolutions and cluster solutions to generate the aggregated spendingprofile (341). The aggregated spending profile (341) can be updated morefrequently than the factor solutions and cluster solutions, when the newtransaction data (109) becomes available. For example, the aggregatedspending profile (341) may be updated quarterly or monthly.

Various tweaks and adjustments can be made for the variables (e.g., 313,315) used for the factor analysis (327) and the cluster analysis (329).For example, the transaction records (301) may be filtered, weighted orconstrained, according to different rules to improve the capabilities ofthe aggregated measurements in indicating certain aspects of thespending behavior of the customers.

For example, in one embodiment, the variables (e.g., 313, 315) arenormalized and/or standardized (e.g., using statistical average, mean,and/or variance).

For example, the variables (e.g., 313, 315) for the aggregatedmeasurements can be tuned, via filtering and weighting, to predict thefuture trend of spending behavior (e.g., for advertisement selection),to identify abnormal behavior (e.g., for fraud prevention), or toidentify a change in spending pattern (e.g., for advertisement audiencemeasurement), etc. The aggregated measurements, the factor values (344),and/or the cluster ID (343) generated from the aggregated measurementscan be used in a transaction profile (127 or 341) to define the behaviorof an account, an individual, a family, etc.

In one embodiment, the transaction data (109) are aged to provide moreweight to recent data than older data. In other embodiments, thetransaction data (109) are reverse aged. In further embodiments, thetransaction data (109) are seasonally adjusted.

In one embodiment, the variables (e.g., 313, 315) are constrained toeliminate extreme outliers. For example, the minimum values and themaximum values of the spending amounts (315) may be constrained based onvalues at certain percentiles (e.g., the value at one percentile as theminimum and the value at 99 percentile as the maximum) and/or certainpredetermined values. In one embodiment, the spending frequencyvariables (313) are constrained based on values at certain percentilesand median values. For example, the minimum value for a spendingfrequency variable (313) may be constrained at P1−k×(M−P1), where P1 isthe one percentile value, M the median value, and k a predeterminedconstant (e.g., 0.1). For example, the maximum value for a spendingfrequency variable (313) may be constrained at P99+a×(P99−M), where P99is the 99 percentile value, M the median value, and k a predeterminedconstant (e.g., 0.1).

In one embodiment, variable pruning is performed to reduce the number ofvariables (e.g., 313, 315) that have less impact on cluster solutionsand/or factor solutions. For example, variables with standard variationless than a predetermined threshold (e.g., 0.1) may be discarded for thepurpose of cluster analysis (329). For example, analysis of variance(ANOVA) can be performed to identify and remove variables that are nomore significant than a predetermined threshold.

The aggregated spending profile (341) can provide information onspending behavior for various application areas, such as marketing,fraud detection and prevention, creditworthiness assessment, loyaltyanalytics, targeting of offers, etc.

For example, clusters can be used to optimize offers for various groupswithin an advertisement campaign. The use of factors and clusters totarget advertisement can improve the speed of producing targetingmodels. For example, using variables based on factors and clusters (andthus eliminating the need to use a large number of convention variables)can improve predictive models and increase efficiency of targeting byreducing the number of variables examined. The variables formulatedbased on factors and/or clusters can be used with other variables tobuild predictive models based on spending behaviors.

In one embodiment, the aggregated spending profile (341) can be used tomonitor risks in transactions. Factor values are typically consistentover time for each entity. An abrupt change in some of the factor valuesmay indicate a change in financial conditions, or a fraudulent use ofthe account. Models formulated using factors and clusters can be used toidentify a series of transactions that do not follow a normal patternspecified by the factor values (344) and/or the cluster ID (343).Potential bankruptcies can be predicted by analyzing the change offactor values over time; and significant changes in spending behaviormay be detected to stop and/or prevent fraudulent activities.

For example, the factor values (344) can be used in regression modelsand/or neural network models for the detection of certain behaviors orpatterns. Since factors are relatively non-collinear, the factors canwork well as independent variables. For example, factors and clusterscan be used as independent variables in tree models.

For example, surrogate accounts can be selected for the construction ofa quasi-control group. For example, for a given account A that is in onecluster, the account B that is closest to the account A in the samecluster can be selected as a surrogate account of the account B. Thecloseness can be determined by certain values in the aggregated spendingprofile (341), such as factor values (344), category distribution (346),etc. For example, a Euclidian distance defined based on the set ofvalues from the aggregated spending profile (341) can be used to comparethe distances between the accounts. Once identified, the surrogateaccount can be used to reduce or eliminate bias in measurements. Forexample, to determine the effect of an advertisement, the spendingpattern response of the account A that is exposed to the advertisementcan be compared to the spending pattern response of the account B thatis not exposed to the advertisement.

For example, the aggregated spending profile (341) can be used insegmentation and/or filtering analysis, such as selecting cardholdershaving similar spending behaviors identified via factors and/or clustersfor targeted advertisement campaigns, and selecting and determining agroup of merchants that could be potentially marketed towardscardholders originating in a given cluster (e.g., for bundled offers).For example, a query interface can be provided to allow the query toidentify a targeted population based on a set of criteria formulatedusing the values of clusters and factors.

For example, the aggregated spending profile (341) can be used in aspending comparison report, such as comparing a sub-population ofinterest against the overall population, determining how clusterdistributions and mean factor values differ, and building reports formerchants and/or issuers for benchmarking purposes. For example, reportscan be generated according to clusters in an automated way for themerchants. For example, the aggregated spending profile (341) can beused in geographic reports by identifying geographic areas wherecardholders shop most frequently and comparing predominant spendinglocations with cardholder residence locations.

In one embodiment, the profile generator (121) provides affinityrelationship data in the transaction profiles (127) so that thetransaction profiles (127) can be shared with business partners withoutcompromising the privacy of the users (101) and the transaction details.

For example, in one embodiment, the profile generator (121) is toidentify clusters of entities (e.g., accounts, cardholders, families,businesses, cities, regions, etc.) based on the spending patterns of theentities. The clusters represent entity segments identified based on thespending patterns of the entities reflected in the transaction data(109) or the transaction records (301).

In one embodiment, the clusters correspond to cells or regions in themathematical space that contain the respective groups of entities. Forexample, the mathematical space representing the characteristics ofusers (101) may be divided into clusters (cells or regions). Forexample, the cluster analysis (329) may identify one cluster in the cellor region that contains a cluster of entity IDs (e.g., 322) in the spacehaving a plurality of dimensions corresponding to the variables (e.g.,313 and 315). For example, a cluster can also be identified as a cell orregion in a space defined by the factors using the factor definitions(331) generated from the factor analysis (327).

In one embodiment, the parameters used in the aggregated spendingprofile (341) can be used to define a segment or a cluster of entities.For example, a value for the cluster ID (343) and a set of ranges forthe factor values (344) and/or other values can be used to define asegment.

In one embodiment, a set of clusters are standardized to represent thepredilection of entities in various groups for certain products orservices. For example, a set of standardized clusters can be formulatedfor people who have shopped, for example, at home improvement stores.The cardholders in the same cluster have similar spending behavior.

In one embodiment, the tendency or likelihood of a user (101) being in aparticular cluster (i.e. the user's affinity to the cell) can becharacterized using a value, based on past purchases. The same user(101) may have different affinity values for different clusters.

For example, a set of affinity values can be computed for an entity,based on the transaction records (301), to indicate the closeness orpredilection of the entity to the set of standardized clusters. Forexample, a cardholder who has a first value representing affinity of thecardholder to a first cluster may have a second value representingaffinity of the cardholder to a second cluster. For example, if aconsumer buys a lot of electronics, the affinity value of the consumerto the electronics cluster is high.

In one embodiment, other indicators are formulated across the merchantcommunity and cardholder behavior and provided in the profile (e.g., 127or 341) to indicate the risk of a transaction.

In one embodiment, the relationship of a pair of values from twodifferent clusters provides an indication of the likelihood that theuser (101) is in one of the two cells, if the user (101) is shown to bein the other cell. For example, if the likelihood of the user (101) topurchase each of two types of products is known, the scores can be usedto determine the likelihood of the user (101) buying one of the twotypes of products if the user (101) is known to be interested in theother type of products. In one embodiment, a map of the values for theclusters is used in a profile (e.g., 127 or 341) to characterize thespending behavior of the user (101) (or other types of entities, such asa family, company, neighborhood, city, or other types of groups definedby other aggregate parameters, such as time of day, etc.).

In one embodiment, the clusters and affinity information arestandardized to allow sharing between business partners, such astransaction processing organizations, search providers, and marketers.Purchase statistics and search statistics are generally described indifferent ways. For example, purchase statistics are based on merchants,merchant categories, SKU numbers, product descriptions, etc.; and searchstatistics are based on search terms. Once the clusters arestandardized, the clusters can be used to link purchase informationbased merchant categories (and/or SKU numbers, product descriptions)with search information based on search terms. Thus, search predilectionand purchase predilection can be mapped to each other.

In one embodiment, the purchase data and the search data (or other thirdparty data) are correlated based on mapping to the standardized clusters(cells or segments). The purchase data and the search data (or otherthird party data) can be used together to provide benefits or offers(e.g., coupons) to consumers. For example, standardized clusters can beused as a marketing tool to provide relevant benefits, includingcoupons, statement credits, or the like to consumers who are within orare associated with common clusters. For example, a data exchangeapparatus may obtain cluster data based on consumer search engine dataand actual payment transaction data to identify like groups ofindividuals who may respond favorably to particular types of benefits,such as coupons and statement credits.

Details about aggregated spending profile (341) in one embodiment areprovided in U.S. Pat. App. Pub. No. 2010/0306032, entitled “Systems andMethods to Summarize Transaction Data,” the disclosure of which ishereby incorporated herein by reference.

Transaction Data Based Portal

In FIG. 1, the transaction terminal (105) initiates the transaction fora user (101) (e.g., a customer) for processing by a transaction handler(103). The transaction handler (103) processes the transaction andstores transaction data (109) about the transaction, in connection withaccount data (111), such as the account profile of an account of theuser (101). The account data (111) may further include data about theuser (101), collected from issuers or merchants, and/or other sources,such as social networks, credit bureaus, merchant provided information,address information, etc. In one embodiment, a transaction may beinitiated by a server (e.g., based on a stored schedule for recurrentpayments).

Over a period of time, the transaction handler (103) accumulates thetransaction data (109) from transactions initiated at differenttransaction terminals (e.g., 105) for different users (e.g., 101). Thetransaction data (109) thus includes information on purchases made byvarious users (e.g., 101) at various times via different purchasesoptions (e.g., online purchase, offline purchase from a retail store,mail order, order via phone, etc.)

In one embodiment, the accumulated transaction data (109) and thecorresponding account data (111) are used to generate intelligenceinformation about the purchase behavior, pattern, preference, tendency,frequency, trend, amount and/or propensity of the users (e.g., 101), asindividuals or as a member of a group. The intelligence information canthen be used to generate, identify and/or select targeted advertisementsfor presentation to the user (101) on the point of interaction (107),during a transaction, after a transaction, or when other opportunitiesarise.

FIG. 4 shows a system to provide information based on transaction data(109) according to one embodiment. In FIG. 4, the transaction handler(103) is coupled between an issuer processor (145) and an acquirerprocessor (147) to facilitate authorization and settlement oftransactions between a consumer account (146) and a merchant account(148). The transaction handler (103) records the transactions in thedata warehouse (149). The portal (143) is coupled to the data warehouse(149) to provide information based on the transaction records (301),such as the transaction profiles (127) or aggregated spending profile(341). The portal (143) may be implemented as a web portal, a telephonegateway, a file/data server, etc.

In one embodiment, the portal (143) is configured to receive queriesidentifying search criteria from the profile selector (129), theadvertisement selector (133) and/or third parties and in response, toprovide transaction-based intelligence requested by the queries.

For example, in one embodiment, a query is to specify a plurality ofaccount holders to request the portal (143) to deliver the transactionprofiles (127) of account holders in a batch mode.

For example, in one embodiment, a query is to identify the user (101) torequest the user specific profile (131), or the aggregated spendingprofile (341), of the user (101). The user (101) may be identified usingthe account data (111), such as the account number (302), or the userdata (125) such as browser cookie ID, IP address, etc.

For example, in one embodiment, a query is to identify a retaillocation; and the portal (143) is to provide a profile (e.g., 341) thatsummarizes the aggregated spending patterns of users who have shopped atthe retail location within a period of time.

For example, in one embodiment, a query is to identify a geographicallocation; and the portal (143) is to provide a profile (e.g., 341) thatsummarizes the aggregated spending patterns of users who have been to,or who are expected to visit, the geographical location within a periodof time (e.g., as determined or predicted based on the locations of thepoint of interactions (e.g., 107) of the users).

For example, in one embodiment, a query is to identify a geographicalarea; and the portal (143) is to provide a profile (e.g., 341) thatsummarizes the aggregated spending patterns of users who reside in thegeographical area (e.g., as determined by the account data (111), or whohave made transactions within the geographical area with a period oftime (e.g., as determined by the locations of the transaction terminals(e.g., 105) used to process the transactions).

In one embodiment, the portal (143) is configured to register certainusers (101) for various programs, such as a loyalty program to providerewards and/or offers to the users (101).

In one embodiment, the portal (143) is to register the interest of users(101), or to obtain permissions from the users (101) to gather furtherinformation about the users (101), such as data capturing purchasedetails, online activities, etc.

In one embodiment, the user (101) may register via the issuer; and theregistration data in the consumer account (146) may propagate to thedata warehouse (149) upon approval from the user (101).

In one embodiment, the portal (143) is to register merchants and provideservices and/or information to merchants.

In one embodiment, the portal (143) is to receive information from thirdparties, such as search engines, merchants, websites, etc. The thirdparty data can be correlated with the transaction data (109) to identifythe relationships between purchases and other events, such as searches,news announcements, conferences, meetings, etc., and improve theprediction capability and accuracy.

In FIG. 4, the consumer account (146) is under the control of the issuerprocessor (145). The consumer account (146) may be owned by anindividual, or an organization such as a business, a school, etc. Theconsumer account (146) may be a credit account, a debit account, or astored value account. The issuer may provide the consumer (e.g., user(101)) an account identification device (141) to identify the consumeraccount (146) using the account information (142). The respectiveconsumer of the account (146) can be called an account holder or acardholder, even when the consumer is not physically issued a card, orthe account identification device (141), in one embodiment. The issuerprocessor (145) is to charge the consumer account (146) to pay forpurchases.

In one embodiment, the account identification device (141) is a plasticcard having a magnetic strip storing account information (142)identifying the consumer account (146) and/or the issuer processor(145). Alternatively, the account identification device (141) is asmartcard having an integrated circuit chip storing at least the accountinformation (142). In one embodiment, the account identification device(141) includes a mobile phone having an integrated smartcard.

In one embodiment, the account information (142) is printed or embossedon the account identification device (141). The account information(142) may be printed as a bar code to allow the transaction terminal(105) to read the information via an optical scanner. The accountinformation (142) may be stored in a memory of the accountidentification device (141) and configured to be read via wireless,contactless communications, such as near field communications viamagnetic field coupling, infrared communications, or radio frequencycommunications. Alternatively, the transaction terminal (105) mayrequire contact with the account identification device (141) to read theaccount information (142) (e.g., by reading the magnetic strip of a cardwith a magnetic strip reader).

In one embodiment, the transaction terminal (105) is configured totransmit an authorization request message to the acquirer processor(147). The authorization request includes the account information (142),an amount of payment, and information about the merchant (e.g., anindication of the merchant account (148)). The acquirer processor (147)requests the transaction handler (103) to process the authorizationrequest, based on the account information (142) received in thetransaction terminal (105). The transaction handler (103) routes theauthorization request to the issuer processor (145) and may process andrespond to the authorization request when the issuer processor (145) isnot available. The issuer processor (145) determines whether toauthorize the transaction based at least in part on a balance of theconsumer account (146).

In one embodiment, the transaction handler (103), the issuer processor(145), and the acquirer processor (147) may each include a subsystem toidentify the risk in the transaction and may reject the transactionbased on the risk assessment.

In one embodiment, the account identification device (141) includessecurity features to prevent unauthorized uses of the consumer account(146), such as a logo to show the authenticity of the accountidentification device (141), encryption to protect the accountinformation (142), etc.

In one embodiment, the transaction terminal (105) is configured tointeract with the account identification device (141) to obtain theaccount information (142) that identifies the consumer account (146)and/or the issuer processor (145). The transaction terminal (105)communicates with the acquirer processor (147) that controls themerchant account (148) of a merchant. The transaction terminal (105) maycommunicate with the acquirer processor (147) via a data communicationconnection, such as a telephone connection, an Internet connection, etc.The acquirer processor (147) is to collect payments into the merchantaccount (148) on behalf of the merchant.

In one embodiment, the transaction terminal (105) is a POS terminal at atraditional, offline, “brick and mortar” retail store. In anotherembodiment, the transaction terminal (105) is an online server thatreceives account information (142) of the consumer account (146) fromthe user (101) through a web connection. In one embodiment, the user(101) may provide account information (142) through a telephone call,via verbal communications with a representative of the merchant; and therepresentative enters the account information (142) into the transactionterminal (105) to initiate the transaction.

In one embodiment, the account information (142) can be entered directlyinto the transaction terminal (105) to make payment from the consumeraccount (146), without having to physically present the accountidentification device (141). When a transaction is initiated withoutphysically presenting an account identification device (141), thetransaction is classified as a “card-not-present” (CNP) transaction.

In one embodiment, the issuer processor (145) may control more than oneconsumer account (146); the acquirer processor (147) may control morethan one merchant account (148); and the transaction handler (103) isconnected between a plurality of issuer processors (e.g., 145) and aplurality of acquirer processors (e.g., 147). An entity (e.g., bank) mayoperate both an issuer processor (145) and an acquirer processor (147).

In one embodiment, the transaction handler (103), the issuer processor(145), the acquirer processor (147), the transaction terminal (105), theportal (143), and other devices and/or services accessing the portal(143) are connected via communications networks, such as local areanetworks, cellular telecommunications networks, wireless wide areanetworks, wireless local area networks, an intranet, and Internet. Inone embodiment, dedicated communication channels are used between thetransaction handler (103) and the issuer processor (145), between thetransaction handler (103) and the acquirer processor (147), and/orbetween the portal (143) and the transaction handler (103).

In one embodiment, the transaction handler (103) uses the data warehouse(149) to store the records about the transactions, such as thetransaction records (301) or transaction data (109). In one embodiment,the transaction handler (103) includes a powerful computer, or clusterof computers functioning as a unit, controlled by instructions stored ona computer readable medium.

In one embodiment, the transaction handler (103) is configured tosupport and deliver authorization services, exception file services, andclearing and settlement services. In one embodiment, the transactionhandler (103) has a subsystem to process authorization requests andanother subsystem to perform clearing and settlement services.

In one embodiment, the transaction handler (103) is configured toprocess different types of transactions, such credit card transactions,debit card transactions, prepaid card transactions, and other types ofcommercial transactions.

In one embodiment, the transaction handler (103) facilitates thecommunications between the issuer processor (145) and the acquirerprocessor (147).

In one embodiment, the transaction handler (103) is coupled to theportal (143) (and/or the profile selector (129), the advertisementselector (133), the media controller (115)) to charge the fees for theservices of providing the transaction-based intelligence informationand/or advertisement.

For example, in one embodiment, the system illustrated in FIG. 1 isconfigured to deliver advertisements to the point of interaction (107)of the user (101), based on the transaction-based intelligenceinformation; and the transaction handler (103) is configured to chargethe advertisement fees to the account of the advertiser in communicationwith the issuer processor in control of the account of the advertiser.The advertisement fees may be charged in response to the presentation ofthe advertisement, or in response to the completion of a pre-determinednumber of presentations, or in response to a transaction resulted fromthe presentation of the advertisement. In one embodiment, thetransaction handler (103) is configured to a periodic fee (e.g., monthlyfee, annual fee) to the account of the advertiser in communication withthe respective issuer processor that is similar to the issuer processor(145) of the consumer account (146).

For example, in one embodiment, the portal (143) is configured toprovide transaction-based intelligence information in response to thequeries received in the portal (143). The portal (143) is to identifythe requesters (e.g., via an authentication, or the address of therequesters) and instruct the transaction handler (103) to charge theconsumer accounts (e.g., 146) of the respective requesters for thetransaction-based intelligence information. In one embodiment, theaccounts of the requesters are charged in response to the delivery ofthe intelligence information via the portal (143). In one embodiment,the accounts of the requesters are charged a periodic subscription feefor the access to the query capability of the portal (143).

In one embodiment, the information service provided by the systemillustrated in FIG. 1 includes multiple parties, such as one entityoperating the transaction handler (103), one entity operating theadvertisement data (135), one entity operating the user tracker (113),one entity operating the media controller (115), etc. The transactionhandler (103) is used to generate transactions to settle the fees,charges and/or divide revenues using the accounts of the respectiveparties. In one embodiment, the account information of the parties isstored in the data warehouse (149) coupled to the transaction handler(103). In some embodiments, a separate billing engine is used togenerate the transactions to settle the fees, charges and/or dividerevenues.

In one embodiment, the transaction terminal (105) is configured tosubmit the authorized transactions to the acquirer processor (147) forsettlement. The amount for the settlement may be different from theamount specified in the authorization request. The transaction handler(103) is coupled between the issuer processor (145) and the acquirerprocessor (147) to facilitate the clearing and settling of thetransaction. Clearing includes the exchange of financial informationbetween the issuer processor (145) and the acquirer processor (147); andsettlement includes the exchange of funds.

In one embodiment, the issuer processor (145) is to provide funds tomake payments on behalf of the consumer account (146). The acquirerprocessor (147) is to receive the funds on behalf of the merchantaccount (148). The issuer processor (145) and the acquirer processor(147) communicate with the transaction handler (103) to coordinate thetransfer of funds for the transaction. In one embodiment, the funds aretransferred electronically.

In one embodiment, the transaction terminal (105) may submit atransaction directly for settlement, without having to separately submitan authorization request.

In one embodiment, the portal (143) provides a user interface to allowthe user (101) to organize the transactions in one or more consumeraccounts (146) of the user with one or more issuers. The user (101) mayorganize the transactions using information and/or categories identifiedin the transaction records (301), such as merchant category (306),transaction date (303), amount (304), etc. Examples and techniques inone embodiment are provided in U.S. Pat. App. Pub. No. 2007/0055597,entitled “Method and System for Manipulating Purchase Information,” thedisclosure of which is hereby incorporated herein by reference.

In one embodiment, the portal (143) provides transaction basedstatistics, such as indicators for retail spending monitoring,indicators for merchant benchmarking, industry/market segmentation,indicators of spending patterns, etc. Further examples can be found inU.S. Pat. App. Pub. No. 2009/0048884, entitled “Merchant BenchmarkingTool,” U.S. patent application Ser. No. 12/940,562, filed Nov. 5, 2010,and U.S. patent application Ser. No. 12/940,664, filed Nov. 5, 2010, thedisclosures of which applications are hereby incorporated herein byreference.

Transaction Terminal

FIG. 5 illustrates a transaction terminal according to one embodiment.In FIG. 5, the transaction terminal (105) is configured to interact withan account identification device (141) to obtain account information(142) about the consumer account (146).

In one embodiment, the transaction terminal (105) includes a memory(167) coupled to the processor (151), which controls the operations of areader (163), an input device (153), an output device (165) and anetwork interface (161). The memory (167) may store instructions for theprocessor (151) and/or data, such as an identification that isassociated with the merchant account (148).

In one embodiment, the reader (163) includes a magnetic strip reader. Inanother embodiment, the reader (163) includes a contactless reader, suchas a radio frequency identification (RFID) reader, a near fieldcommunications (NFC) device configured to read data via magnetic fieldcoupling (in accordance with ISO standard 14443/NFC), a Bluetoothtransceiver, a WiFi transceiver, an infrared transceiver, a laserscanner, etc.

In one embodiment, the input device (153) includes key buttons that canbe used to enter the account information (142) directly into thetransaction terminal (105) without the physical presence of the accountidentification device (141). The input device (153) can be configured toprovide further information to initiate a transaction, such as apersonal identification number (PIN), password, zip code, etc. that maybe used to access the account identification device (141), or incombination with the account information (142) obtained from the accountidentification device (141).

In one embodiment, the output device (165) may include a display, aspeaker, and/or a printer to present information, such as the result ofan authorization request, a receipt for the transaction, anadvertisement, etc.

In one embodiment, the network interface (161) is configured tocommunicate with the acquirer processor (147) via a telephoneconnection, an Internet connection, or a dedicated data communicationchannel.

In one embodiment, the instructions stored in the memory (167) areconfigured at least to cause the transaction terminal (105) to send anauthorization request message to the acquirer processor (147) toinitiate a transaction. The transaction terminal (105) may or may notsend a separate request for the clearing and settling of thetransaction. The instructions stored in the memory (167) are alsoconfigured to cause the transaction terminal (105) to perform othertypes of functions discussed in this description.

In one embodiment, a transaction terminal (105) may have fewercomponents than those illustrated in FIG. 5. For example, in oneembodiment, the transaction terminal (105) is configured for“card-not-present” transactions; and the transaction terminal (105) doesnot have a reader (163).

In one embodiment, a transaction terminal (105) may have more componentsthan those illustrated in FIG. 5. For example, in one embodiment, thetransaction terminal (105) is an ATM machine, which includes componentsto dispense cash under certain conditions.

Account Identification Device

FIG. 6 illustrates an account identifying device according to oneembodiment. In FIG. 6, the account identification device (141) isconfigured to carry account information (142) that identifies theconsumer account (146).

In one embodiment, the account identification device (141) includes amemory (167) coupled to the processor (151), which controls theoperations of a communication device (159), an input device (153), anaudio device (157) and a display device (155). The memory (167) maystore instructions for the processor (151) and/or data, such as theaccount information (142) associated with the consumer account (146).

In one embodiment, the account information (142) includes an identifieridentifying the issuer (and thus the issuer processor (145)) among aplurality of issuers, and an identifier identifying the consumer accountamong a plurality of consumer accounts controlled by the issuerprocessor (145). The account information (142) may include an expirationdate of the account identification device (141), the name of theconsumer holding the consumer account (146), and/or an identifieridentifying the account identification device (141) among a plurality ofaccount identification devices associated with the consumer account(146).

In one embodiment, the account information (142) may further include aloyalty program account number, accumulated rewards of the consumer inthe loyalty program, an address of the consumer, a balance of theconsumer account (146), transit information (e.g., a subway or trainpass), access information (e.g., access badges), and/or consumerinformation (e.g., name, date of birth), etc.

In one embodiment, the memory includes a nonvolatile memory, such asmagnetic strip, a memory chip, a flash memory, a Read Only Memory (ROM),etc. to store the account information (142).

In one embodiment, the information stored in the memory (167) of theaccount identification device (141) may also be in the form of datatracks that are traditionally associated with credits cards. Such tracksinclude Track 1 and Track 2. Track 1 (“International Air TransportAssociation”) stores more information than Track 2, and contains thecardholder's name as well as the account number and other discretionarydata. Track 1 is sometimes used by airlines when securing reservationswith a credit card. Track 2 (“American Banking Association”) iscurrently most commonly used and is read by ATMs and credit cardcheckers. The ABA (American Banking Association) designed thespecifications of Track 1 and banks abide by it. It contains thecardholder's account number, encrypted PIN, and other discretionarydata.

In one embodiment, the communication device (159) includes asemiconductor chip to implement a transceiver for communication with thereader (163) and an antenna to provide and/or receive wireless signals.

In one embodiment, the communication device (159) is configured tocommunicate with the reader (163). The communication device (159) mayinclude a transmitter to transmit the account information (142) viawireless transmissions, such as radio frequency signals, magneticcoupling, or infrared, Bluetooth or WiFi signals, etc.

In one embodiment, the account identification device (141) is in theform of a mobile phone, personal digital assistant (PDA), etc. The inputdevice (153) can be used to provide input to the processor (151) tocontrol the operation of the account identification device (141); andthe audio device (157) and the display device (155) may present statusinformation and/or other information, such as advertisements or offers.The account identification device (141) may include further componentsthat are not shown in FIG. 6, such as a cellular communicationssubsystem.

In one embodiment, the communication device (159) may access the accountinformation (142) stored on the memory (167) without going through theprocessor (151).

In one embodiment, the account identification device (141) has fewercomponents than those illustrated in FIG. 6. For example, an accountidentification device (141) does not have the input device (153), theaudio device (157) and the display device (155) in one embodiment; andin another embodiment, an account identification device (141) does nothave components (151-159).

For example, in one embodiment, an account identification device (141)is in the form of a debit card, a credit card, a smartcard, or aconsumer device that has optional features such as magnetic strips, orsmartcards.

An example of an account identification device (141) is a magnetic stripattached to a plastic substrate in the form of a card. The magneticstrip is used as the memory (167) of the account identification device(141) to provide the account information (142). Consumer information,such as account number, expiration date, and consumer name may beprinted or embossed on the card. A semiconductor chip implementing thememory (167) and the communication device (159) may also be embedded inthe plastic card to provide account information (142) in one embodiment.In one embodiment, the account identification device (141) has thesemiconductor chip but not the magnetic strip.

In one embodiment, the account identification device (141) is integratedwith a security device, such as an access card, a radio frequencyidentification (RFID) tag, a security card, a transponder, etc.

In one embodiment, the account identification device (141) is a handheldand compact device. In one embodiment, the account identification device(141) has a size suitable to be placed in a wallet or pocket of theconsumer.

Some examples of an account identification device (141) include a creditcard, a debit card, a stored value device, a payment card, a gift card,a smartcard, a smart media card, a payroll card, a health care card, awrist band, a keychain device, a supermarket discount card, atransponder, and a machine readable medium containing accountinformation (142).

Point of Interaction

In one embodiment, the point of interaction (107) is to provide anadvertisement to the user (101), or to provide information derived fromthe transaction data (109) to the user (101).

In one embodiment, an advertisement is a marketing interaction which mayinclude an announcement and/or an offer of a benefit, such as adiscount, incentive, reward, coupon, gift, cash back, or opportunity(e.g., special ticket/admission). An advertisement may include an offerof a product or service, an announcement of a product or service, or apresentation of a brand of products or services, or a notice of events,facts, opinions, etc. The advertisements can be presented in text,graphics, audio, video, or animation, and as printed matter, webcontent, interactive media, etc. An advertisement may be presented inresponse to the presence of a financial transaction card, or in responseto a financial transaction card being used to make a financialtransaction, or in response to other user activities, such as browsing aweb page, submitting a search request, communicating online, entering awireless communication zone, etc. In one embodiment, the presentation ofadvertisements may be not a result of a user action.

In one embodiment, the point of interaction (107) can be one of variousendpoints of the transaction network, such as point of sale (POS)terminals, automated teller machines (ATMs), electronic kiosks (orcomputer kiosks or interactive kiosks), self-assist checkout terminals,vending machines, gas pumps, websites of banks (e.g., issuer banks oracquirer banks of credit cards), bank statements (e.g., credit cardstatements), websites of the transaction handler (103), websites ofmerchants, checkout websites or web pages for online purchases, etc.

In one embodiment, the point of interaction (107) may be the same as thetransaction terminal (105), such as a point of sale (POS) terminal, anautomated teller machine (ATM), a mobile phone, a computer of the userfor an online transaction, etc. In one embodiment, the point ofinteraction (107) may be co-located with, or near, the transactionterminal (105) (e.g., a video monitor or display, a digital sign), orproduced by the transaction terminal (e.g., a receipt produced by thetransaction terminal (105)). In one embodiment, the point of interaction(107) may be separate from and not co-located with the transactionterminal (105), such as a mobile phone, a personal digital assistant, apersonal computer of the user, a voice mail box of the user, an emailinbox of the user, a digital sign, etc.

For example, the advertisements can be presented on a portion of mediafor a transaction with the customer, which portion might otherwise beunused and thus referred to as a “white space” herein. A white space canbe on a printed matter (e.g., a receipt printed for the transaction, ora printed credit card statement), on a video display (e.g., a displaymonitor of a POS terminal for a retail transaction, an ATM for cashwithdrawal or money transfer, a personal computer of the customer foronline purchases), or on an audio channel (e.g., an interactive voiceresponse (IVR) system for a transaction over a telephonic device).

In one embodiment, the white space is part of a media channel availableto present a message from the transaction handler (103) in connectionwith the processing of a transaction of the user (101). In oneembodiment, the white space is in a media channel that is used to reportinformation about a transaction of the user (101), such as anauthorization status, a confirmation message, a verification message, auser interface to verify a password for the online use of the accountinformation (142), a monthly statement, an alert or a report, or a webpage provided by the portal (143) to access a loyalty program associatedwith the consumer account (146) or a registration program.

In other embodiments, the advertisements can also be presented via othermedia channels which may not involve a transaction processed by thetransaction handler (103). For example, the advertisements can bepresented on publications or announcements (e.g., newspapers, magazines,books, directories, radio broadcasts, television, digital signage, etc.,which may be in an electronic form, or in a printed or painted form).The advertisements may be presented on paper, on websites, onbillboards, on digital signs, or on audio portals.

In one embodiment, the transaction handler (103) purchases the rights touse the media channels from the owner or operators of the media channelsand uses the media channels as advertisement spaces. For example, whitespaces at a point of interaction (e.g., 107) with customers fortransactions processed by the transaction handler (103) can be used todeliver advertisements relevant to the customers conducting thetransactions; and the advertisement can be selected based at least inpart on the intelligence information derived from the accumulatedtransaction data (109) and/or the context at the point of interaction(107) and/or the transaction terminal (105).

In general, a point of interaction (e.g., 107) may or may not be capableof receiving inputs from the customers, and may or may not co-locatedwith a transaction terminal (e.g., 105) that initiates the transactions.The white spaces for presenting the advertisement on the point ofinteraction (107) may be on a portion of a geographical display space(e.g., on a screen), or on a temporal space (e.g., in an audio stream).

In one embodiment, the point of interaction (107) may be used toprimarily to access services not provided by the transaction handler(103), such as services provided by a search engine, a social networkingwebsite, an online marketplace, a blog, a news site, a televisionprogram provider, a radio station, a satellite, a publisher, etc.

In one embodiment, a consumer device is used as the point of interaction(107), which may be a non-portable consumer device or a portablecomputing device. The consumer device is to provide media content to theuser (101) and may receive input from the user (101).

Examples of non-portable consumer devices include a computer terminal, atelevision set, a personal computer, a set-top box, or the like.Examples of portable consumer devices include a portable computer, acellular phone, a personal digital assistant (PDA), a pager, a securitycard, a wireless terminal, or the like. The consumer device may beimplemented as a data processing system as illustrated in FIG. 7, withmore or fewer components.

In one embodiment, the consumer device includes an accountidentification device (141). For example, a smart card used as anaccount identification device (141) is integrated with a mobile phone,or a personal digital assistant (PDA).

In one embodiment, the point of interaction (107) is integrated with atransaction terminal (105). For example, a self-service checkoutterminal includes a touch pad to interact with the user (101); and anATM machine includes a user interface subsystem to interact with theuser (101).

Hardware

In one embodiment, a computing apparatus is configured to include someof the modules or components illustrated in FIGS. 1 and 4, such as thetransaction handler (103), the profile generator (121), the mediacontroller (115), the portal (143), the profile selector (129), theadvertisement selector (133), the user tracker (113), the correlator,and their associated storage devices, such as the data warehouse (149).

In one embodiment, at least some of the modules or componentsillustrated in FIGS. 1 and 4, such as the transaction handler (103), thetransaction terminal (105), the point of interaction (107), the usertracker (113), the media controller (115), the correlator (117), theprofile generator (121), the profile selector (129), the advertisementselector (133), the portal (143), the issuer processor (145), theacquirer processor (147), and the account identification device (141),can be implemented as a computer system, such as a data processingsystem illustrated in FIG. 7, with more or fewer components. Some of themodules may share hardware or be combined on a computer system. In oneembodiment, a network of computers can be used to implement one or moreof the modules.

Further, the data illustrated in FIG. 1, such as transaction data (109),account data (111), transaction profiles (127), and advertisement data(135), can be stored in storage devices of one or more computersaccessible to the corresponding modules illustrated in FIG. 1. Forexample, the transaction data (109) can be stored in the data warehouse(149) that can be implemented as a data processing system illustrated inFIG. 7, with more or fewer components.

In one embodiment, the transaction handler (103) is a payment processingsystem, or a payment card processor, such as a card processor for creditcards, debit cards, etc.

FIG. 7 illustrates a data processing system according to one embodiment.While FIG. 7 illustrates various components of a computer system, it isnot intended to represent any particular architecture or manner ofinterconnecting the components. One embodiment may use other systemsthat have fewer or more components than those shown in FIG. 7.

In FIG. 7, the data processing system (170) includes an inter-connect(171) (e.g., bus and system core logic), which interconnects amicroprocessor(s) (173) and memory (167). The microprocessor (173) iscoupled to cache memory (179) in the example of FIG. 7.

In one embodiment, the inter-connect (171) interconnects themicroprocessor(s) (173) and the memory (167) together and alsointerconnects them to input/output (I/O) device(s) (175) via I/Ocontroller(s) (177). I/O devices (175) may include a display deviceand/or peripheral devices, such as mice, keyboards, modems, networkinterfaces, printers, scanners, video cameras and other devices known inthe art. In one embodiment, when the data processing system is a serversystem, some of the I/O devices (175), such as printers, scanners, mice,and/or keyboards, are optional.

In one embodiment, the inter-connect (171) includes one or more busesconnected to one another through various bridges, controllers and/oradapters. In one embodiment the I/O controllers (177) include a USB(Universal Serial Bus) adapter for controlling USB peripherals, and/oran IEEE-1394 bus adapter for controlling IEEE-1394 peripherals.

In one embodiment, the memory (167) includes one or more of: ROM (ReadOnly Memory), volatile RAM (Random Access Memory), and non-volatilememory, such as hard drive, flash memory, etc.

Volatile RAM is typically implemented as dynamic RAM (DRAM) whichrequires power continually in order to refresh or maintain the data inthe memory. Non-volatile memory is typically a magnetic hard drive, amagnetic optical drive, an optical drive (e.g., a DVD RAM), or othertype of memory system which maintains data even after power is removedfrom the system. The non-volatile memory may also be a random accessmemory.

The non-volatile memory can be a local device coupled directly to therest of the components in the data processing system. A non-volatilememory that is remote from the system, such as a network storage devicecoupled to the data processing system through a network interface suchas a modem or Ethernet interface, can also be used.

In this description, some functions and operations are described asbeing performed by or caused by software code to simplify description.However, such expressions are also used to specify that the functionsresult from execution of the code/instructions by a processor, such as amicroprocessor.

Alternatively, or in combination, the functions and operations asdescribed here can be implemented using special purpose circuitry, withor without software instructions, such as using Application-SpecificIntegrated Circuit (ASIC) or Field-Programmable Gate Array (FPGA).Embodiments can be implemented using hardwired circuitry withoutsoftware instructions, or in combination with software instructions.Thus, the techniques are limited neither to any specific combination ofhardware circuitry and software, nor to any particular source for theinstructions executed by the data processing system.

While one embodiment can be implemented in fully functioning computersand computer systems, various embodiments are capable of beingdistributed as a computing product in a variety of forms and are capableof being applied regardless of the particular type of machine orcomputer-readable media used to actually effect the distribution.

At least some aspects disclosed can be embodied, at least in part, insoftware. That is, the techniques may be carried out in a computersystem or other data processing system in response to its processor,such as a microprocessor, executing sequences of instructions containedin a memory, such as ROM, volatile RAM, non-volatile memory, cache or aremote storage device.

Routines executed to implement the embodiments may be implemented aspart of an operating system or a specific application, component,program, object, module or sequence of instructions referred to as“computer programs.” The computer programs typically include one or moreinstructions set at various times in various memory and storage devicesin a computer, and that, when read and executed by one or moreprocessors in a computer, cause the computer to perform operationsnecessary to execute elements involving the various aspects.

A machine readable medium can be used to store software and data whichwhen executed by a data processing system causes the system to performvarious methods. The executable software and data may be stored invarious places including for example ROM, volatile RAM, non-volatilememory and/or cache. Portions of this software and/or data may be storedin any one of these storage devices. Further, the data and instructionscan be obtained from centralized servers or peer to peer networks.Different portions of the data and instructions can be obtained fromdifferent centralized servers and/or peer to peer networks at differenttimes and in different communication sessions or in a same communicationsession. The data and instructions can be obtained in entirety prior tothe execution of the applications. Alternatively, portions of the dataand instructions can be obtained dynamically, just in time, when neededfor execution. Thus, it is not required that the data and instructionsbe on a machine readable medium in entirety at a particular instance oftime.

Examples of computer-readable media include but are not limited torecordable and non-recordable type media such as volatile andnon-volatile memory devices, read only memory (ROM), random accessmemory (RAM), flash memory devices, floppy and other removable disks,magnetic disk storage media, optical storage media (e.g., Compact DiskRead-Only Memory (CDROM), Digital Versatile Disks (DVDs), etc.), amongothers. The computer-readable media may store the instructions.

The instructions may also be embodied in digital and analogcommunication links for electrical, optical, acoustical or other formsof propagated signals, such as carrier waves, infrared signals, digitalsignals, etc. However, propagated signals, such as carrier waves,infrared signals, digital signals, etc. are not tangible machinereadable medium and are not configured to store instructions.

In general, a machine readable medium includes any mechanism thatprovides (i.e., stores and/or transmits) information in a formaccessible by a machine (e.g., a computer, network device, personaldigital assistant, manufacturing tool, any device with a set of one ormore processors, etc.).

In various embodiments, hardwired circuitry may be used in combinationwith software instructions to implement the techniques. Thus, thetechniques are neither limited to any specific combination of hardwarecircuitry and software nor to any particular source for the instructionsexecuted by the data processing system.

Other Aspects

The description and drawings are illustrative and are not to beconstrued as limiting. Numerous specific details are described toprovide a thorough understanding. However, in certain instances, wellknown or conventional details are not described in order to avoidobscuring the description. References to one or an embodiment in thepresent disclosure are not necessarily references to the sameembodiment; and, such references mean at least one.

The use of headings herein is merely provided for ease of reference, andshall not be interpreted in any way to limit this disclosure or thefollowing claims.

Reference to “one embodiment” or “an embodiment” means that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the disclosure. Theappearances of the phrase “in one embodiment” in various places in thespecification are not necessarily all referring to the same embodiment,and are not necessarily all referring to separate or alternativeembodiments mutually exclusive of other embodiments. Moreover, variousfeatures are described which may be exhibited by one embodiment and notby others. Similarly, various requirements are described which may berequirements for one embodiment but not other embodiments. Unlessexcluded by explicit description and/or apparent incompatibility, anycombination of various features described in this description is alsoincluded here.

The disclosures of the above discussed patent documents are herebyincorporated herein by reference.

In the foregoing specification, the disclosure has been described withreference to specific exemplary embodiments thereof. It will be evidentthat various modifications may be made thereto without departing fromthe broader spirit and scope as set forth in the following claims. Thespecification and drawings are, accordingly, to be regarded in anillustrative sense rather than a restrictive sense.

What is claimed is:
 1. A computer-implemented method, comprising:providing, a computing device having: a transaction terminal configuredin an electronic payment processing network in which a transactionhandler of the electronic payment processing network interconnects:first computers controlling consumer accounts from which paymenttransactions are made, and second computers controlling merchantaccounts to which the payment transactions are made, wherein: a datawarehouse coupled with the transaction handler stores transaction datarecording the payment transactions processed via the transaction handlerin the electronic payment processing network, a gateway coupled with thetransaction handler communicates outside the electronic paymentprocessing network, a data services platform is coupled with the datawarehouse, the transaction handler processes transactions of a traveler,each of the transactions being processed to make a payment from arespective issuer to a respective acquirer via the transaction handlerin response to an account identifier of the traveler, as issued by therespective issuer, being submitted by a merchant to the respectiveacquirer, the respective issuer to make the payment on behalf of thetraveler, the respective acquirer to receive the payment on behalf ofthe merchant, and a value score of the traveler is computed based on thetransactions processed by the transaction handler, the value scoreindicative of a value of the traveler to merchants of a predeterminedtype; memory storing instructions which, when executed on thetransaction terminal, causes the transaction terminal to perform themethod; receiving, in the transaction terminal, the account identifierfrom an account identification device of the traveler; transmitting, bythe transaction terminal into the electronic payment processing network,a request for authorization of a payment transaction initiated using theaccount identifier between a first merchant of the predetermined typeand the traveler, wherein the transaction handler: processes the requestin the electronic payment processing network, and provides to thegateway a transaction alert according to the payment transaction;communicating, by the computing device with the data services platformoutside the electronic payment processing network in response to thetransaction alert, to receive the value score of the traveler; andproviding, by the computing device, a benefit to the traveler inaccordance with the value score.
 2. The method of claim 1, furthercomprising: checking, by the computing device, the traveler into a hoteloperated by the first merchant in response to the authorization of thepayment transaction.
 3. The method of claim 2, wherein the merchantsprovide hotel services.
 4. The method of claim 3, wherein the benefitincludes an offer to the traveler; and the benefit is computed as afunction of the value score.
 5. The method of claim 1, furthercomprising: registering the traveler based on the account identifier. 6.The method of claim 1, further comprising: enrolling the traveler in aprogram that provides travel related incentives to the travelers who areenrolled in the program.
 7. The method of claim 1, wherein the valuescore is based on data identifying one or more events related to travel.8. The method of claim 1, wherein the benefit includes one of: anupgrade, a reward, a discount, and an incentive.
 9. The method of claim1, wherein the benefit is provided in response to the value score to beabove a threshold.
 10. The method of claim 1, further comprising:reducing the benefit in response to a determination that the value scoreis below a threshold.
 11. A non-transitory computer storage mediumstoring instructions configured to instruct a computing device toperform a method, the method comprising: receiving, in a transactionterminal of the computing device, an account identifier from an accountidentification device of a traveler, wherein the transaction terminal isconfigured in an electronic payment processing network in which atransaction handler of the electronic payment processing networkinterconnects: first computers controlling consumer accounts from whichpayment transactions are made, and second computers controlling merchantaccounts to which the payment transactions are made, wherein: a datawarehouse coupled with the transaction handler stores transaction datarecording the payment transactions processed via the transaction handlerin the electronic payment processing network, a gateway coupled with thetransaction handler communicates outside the electronic paymentprocessing network, a data services platform is coupled with the datawarehouse, the transaction handler processes transactions of thetraveler, each of the transactions being processed to make a paymentfrom a respective issuer to a respective acquirer via the transactionhandler in response to the account identifier of the traveler, as issuedby the respective issuer, being submitted by a merchant to therespective acquirer, the respective issuer to make the payment on behalfof the traveler, the respective acquirer to receive the payment onbehalf of the merchant, and a value score of the traveler is computedbased on the transactions processed by the transaction handler, thevalue score indicative of a value of the traveler to merchants of apredetermined type; transmitting, by the transaction terminal into theelectronic payment processing network, a request for authorization of apayment transaction initiated using the account identifier between afirst merchant of the predetermined type and the traveler, wherein thetransaction handler: processes the request in the electronic paymentprocessing network, and provides to the gateway a transaction alertaccording to the payment transaction; communicating, by the computingdevice with the data services platform outside the electronic paymentprocessing network, to receive the value score of the traveler inresponse to the transaction alert; and providing, by the computingdevice, a benefit to the traveler in accordance with the value score.12. The medium of claim 11, wherein the method further comprises:registering the traveler based on the account identifier.
 13. The mediumof claim 11, wherein the benefit includes one of: an upgrade, a reward,a discount, and an incentive.
 14. The medium of claim 11, wherein themethod further comprises: enrolling the traveler in a program.
 15. Acomputing device, comprising: a transaction handler configured in anelectronic payment processing network in which the transaction handlerinterconnects: first computers controlling consumer accounts from whichpayment transactions are made, and second computers controlling merchantaccounts to which the payment transactions are made; a data warehousecoupled with the transaction handler and storing transaction datarecording the payment transactions processed via the transaction handlerin the electronic payment processing network; a gateway coupled with thetransaction handler and configured to communicate outside the electronicpayment processing network; and a data services platform coupled withthe data warehouse; wherein in response to the transaction handlerprocesses a payment transaction initiated, in the electronic paymentprocessing network using an account identifier of a traveler, between amerchant of a predetermined category and the traveler, the transactionhandler communicates, to the gateway of the computing device, atransaction alert according to the payment transaction; and the dataservices platform communicates, in accordance with the transaction alertand outside the electronic payment processing network, a value score ofthe traveler to a terminal of the merchant of the predeterminedcategory, the value score indicative of a value of the traveler tomerchants of the predetermined category according to the transactiondata; wherein the terminal of the merchant provides a benefit to thetraveler in response to the value score and in connection with thepayment transaction.
 16. The computing device of claim 15, wherein thecomputing device computes a value score of a traveler based on:transactions processed by the transaction handler for the traveler, anddetection of an event separate from payment transactions and independentfrom the traveler.
 17. The computing device of claim 16, wherein thevalue score is based at least in part on a statistical cause and effectrelation between the event and transactions in the predeterminedcategory.
 18. The computing device of claim 15, wherein the benefitincludes one of: an upgrade, a reward, a discount, and an incentive. 19.The computing device of claim 18, wherein the benefit is reduced whenthe value score is below a threshold.
 20. The computing device of claim15, wherein, in response to the payment transaction, the terminal checksthe traveler in.